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Search Results for 'Data Science' (433 products)

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Principles of Data Science
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Principles of Data Science
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Jan 2024
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (4)
Paperback 326 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (4)
A beginner's guide to essential math and coding skills for data fluency and machine learning
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  • 9781837636006 eBook $31.99
  • 9781837636303 Paperback $39.99
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Principles of Data Science
A beginner's guide to essential math and coding skills for data fluency and machine learning
Description
Principles of Data Science bridges mathematics, programming, and business analysis, empowering you to confidently pose and address complex data questions and construct effective machine learning pipelines. This book will equip you with the tools to transform abstract concepts and raw statistics into actionable insights. Starting with cleaning and preparation, you’ll explore effective data mining strategies and techniques before moving on to building a holistic picture of how every piece of the data science puzzle fits together. Throughout the book, you’ll discover statistical models with which you can control and navigate even the densest or the sparsest of datasets and learn how to create powerful visualizations that communicate the stories hidden in your data. With a focus on application, this edition covers advanced transfer learning and pre-trained models for NLP and vision tasks. You’ll get to grips with advanced techniques for mitigating algorithmic bias in data as well as models and addressing model and data drift. Finally, you’ll explore medium-level data governance, including data provenance, privacy, and deletion request handling. By the end of this data science book, you'll have learned the fundamentals of computational mathematics and statistics, all while navigating the intricacies of modern ML and large pre-trained models like GPT and BERT.
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Jan 2024 326 pages
AI Assistant AI Assistant
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Author Sinan Ozdemir
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Cracking the Data Science Interview
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Cracking the Data Science Interview
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Feb 2024
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (6)
Paperback 404 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (6)
Unlock insider tips from industry experts to master the data science field
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  • 9781805120193 eBook $23.99
  • 9781805120506 Paperback $29.99
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Cracking the Data Science Interview
Unlock insider tips from industry experts to master the data science field
Description
The data science job market is saturated with professionals of all backgrounds, including academics, researchers, bootcampers, and Massive Open Online Course (MOOC) graduates. This poses a challenge for companies seeking the best person to fill their roles. At the heart of this selection process is the data science interview, a crucial juncture that determines the best fit for both the candidate and the company. Cracking the Data Science Interview provides expert guidance on approaching the interview process with full preparation and confidence. Starting with an introduction to the modern data science landscape, you’ll find tips on job hunting, resume writing, and creating a top-notch portfolio. You’ll then advance to topics such as Python, SQL databases, Git, and productivity with shell scripting and Bash. Building on this foundation, you'll delve into the fundamentals of statistics, laying the groundwork for pre-modeling concepts, machine learning, deep learning, and generative AI. The book concludes by offering insights into how best to prepare for the intensive data science interview. By the end of this interview guide, you’ll have gained the confidence, business acumen, and technical skills required to distinguish yourself within this competitive landscape and land your next data science job.
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Feb 2024 404 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Leondra R. Gonzalez
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Streamlit for Data Science
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Streamlit for Data Science
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Sep 2023
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (32)
Paperback 300 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (32)
Create interactive data apps in Python
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  • 9781803232959 eBook $43.99
  • 9781803248226 Paperback $54.99
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Streamlit for Data Science
Create interactive data apps in Python
Description
If you work with data in Python and are looking to create data apps that showcase ML models and make beautiful interactive visualizations, then this is the ideal book for you. Streamlit for Data Science, Second Edition, shows you how to create and deploy data apps quickly, all within Python. This helps you create prototypes in hours instead of days! Written by a prolific Streamlit user and senior data scientist at Snowflake, this fully updated second edition builds on the practical nature of the previous edition with exciting updates, including connecting Streamlit to data warehouses like Snowflake, integrating Hugging Face and OpenAI models into your apps, and connecting and building apps on top of Streamlit databases. Plus, there is a totally updated code repository on GitHub to help you practice your newfound skills. You'll start your journey with the fundamentals of Streamlit and gradually build on this foundation by working with machine learning models and producing high-quality interactive apps. The practical examples of both personal data projects and work-related data-focused web applications will help you get to grips with more challenging topics such as Streamlit Components, beautifying your apps, and quick deployment. By the end of this book, you'll be able to create dynamic web apps in Streamlit quickly and effortlessly.
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Sep 2023
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
300 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Tyler Richards
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Data Science with .NET and Polyglot Notebooks
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Data Science with .NET and Polyglot Notebooks
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Aug 2024
Paperback 404 pages
Programmer's guide to data science using ML.NET, OpenAI, and Semantic Kernel
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  • 9781835882979 eBook $38.99
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Data Science with .NET and Polyglot Notebooks
Programmer's guide to data science using ML.NET, OpenAI, and Semantic Kernel
Description
As the fields of data science, machine learning, and artificial intelligence rapidly evolve, .NET developers are eager to leverage their expertise to dive into these exciting domains but are often unsure of how to do so. Data Science in .NET with Polyglot Notebooks is the practical guide you need to seamlessly bring your .NET skills into the world of analytics and AI. With Microsoft’s .NET platform now robustly supporting machine learning and AI tasks, the introduction of tools such as .NET Interactive kernels and Polyglot Notebooks has opened up a world of possibilities for .NET developers. This book empowers you to harness the full potential of these cutting-edge technologies, guiding you through hands-on experiments that illustrate key concepts and principles. Through a series of interactive notebooks, you’ll not only master technical processes but also discover how to integrate these new skills into your current role or pivot to exciting opportunities in the data science field. By the end of the book, you’ll have acquired the necessary knowledge and confidence to apply cutting-edge data science techniques and deliver impactful solutions within the .NET ecosystem.
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Aug 2024 404 pages
AI Assistant AI Assistant
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Author Matt Eland
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Applied Geospatial Data Science with Python
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Applied Geospatial Data Science with Python
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Feb 2023
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (9)
Paperback 308 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (9)
Leverage geospatial data analysis and modeling to find unique solutions to environmental problems
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  • 9781803240343 eBook $43.99
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Applied Geospatial Data Science with Python
Leverage geospatial data analysis and modeling to find unique solutions to environmental problems
Description
Data scientists, when presented with a myriad of data, can often lose sight of how to present geospatial analyses in a meaningful way so that it makes sense to everyone. Using Python to visualize data helps stakeholders in less technical roles to understand the problem and seek solutions. The goal of this book is to help data scientists and GIS professionals learn and implement geospatial data science workflows using Python. Throughout this book, you’ll uncover numerous geospatial Python libraries with which you can develop end-to-end spatial data science workflows. You’ll learn how to read, process, and manipulate spatial data effectively. With data in hand, you’ll move on to crafting spatial data visualizations to better understand and tell the story of your data through static and dynamic mapping applications. As you progress through the book, you’ll find yourself developing geospatial AI and ML models focused on clustering, regression, and optimization. The use cases can be leveraged as building blocks for more advanced work in a variety of industries. By the end of the book, you’ll be able to tackle random data, find meaningful correlations, and make geospatial data models.
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Feb 2023 308 pages
AI Assistant AI Assistant
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Author David S. Jordan
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Data Science for Decision Makers
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Data Science for Decision Makers
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Jul 2024
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (5)
Paperback 270 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (5)
Enhance your leadership skills with data science and AI expertise
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  • 9781837638345 eBook $35.99
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Data Science for Decision Makers
Enhance your leadership skills with data science and AI expertise
Description
As data science and artificial intelligence (AI) become prevalent across industries, executives without formal education in statistics and machine learning, as well as data scientists moving into leadership roles, must learn how to make informed decisions about complex models and manage data teams. This book will elevate your leadership skills by guiding you through the core concepts of data science and AI. This comprehensive guide is designed to bridge the gap between business needs and technical solutions, empowering you to make informed decisions and drive measurable value within your organization. Through practical examples and clear explanations, you'll learn how to collect and analyze structured and unstructured data, build a strong foundation in statistics and machine learning, and evaluate models confidently. By recognizing common pitfalls and valuable use cases, you'll plan data science projects effectively, from the ground up to completion. Beyond technical aspects, this book provides tools to recruit top talent, manage high-performing teams, and stay up to date with industry advancements. By the end of this book, you’ll be able to characterize the data within your organization and frame business problems as data science problems.
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Jul 2024 270 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Howells
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Practical Data Science with Python
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Practical Data Science with Python
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Sep 2021
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (19)
Paperback 620 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (19)
Learn tools and techniques from hands-on examples to extract insights from data
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Paperback eBook
  • 9781801076654 eBook $43.99
  • 9781801071970 Paperback $54.99
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Practical Data Science with Python
Learn tools and techniques from hands-on examples to extract insights from data
Description
Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science. The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by working through the examples. The code has been broken down into small chunks (a few lines or a function at a time) to enable thorough discussion. As you progress, you will learn how to perform data analysis while exploring the functionalities of key data science Python packages, including pandas, SciPy, and scikit-learn. Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments. By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source.
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Sep 2021 620 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Nathan George
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Building Data Science Applications with FastAPI
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Building Data Science Applications with FastAPI
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Jul 2023
Full star icon Full star icon Full star icon Full star icon Half star icon 4.2 (9)
Paperback 422 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.2 (9)
Develop, manage, and deploy efficient machine learning applications with Python
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  • 9781837637263 eBook $39.99
  • 9781837632749 Paperback $49.99
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Building Data Science Applications with FastAPI
Develop, manage, and deploy efficient machine learning applications with Python
Description
Building Data Science Applications with FastAPI is the go-to resource for creating efficient and dependable data science API backends. This second edition incorporates the latest Python and FastAPI advancements, along with two new AI projects – a real-time object detection system and a text-to-image generation platform using Stable Diffusion. The book starts with the basics of FastAPI and modern Python programming. You'll grasp FastAPI's robust dependency injection system, which facilitates seamless database communication, authentication implementation, and ML model integration. As you progress, you'll learn testing and deployment best practices, guaranteeing high-quality, resilient applications. Throughout the book, you'll build data science applications using FastAPI with the help of projects covering common AI use cases, such as object detection and text-to-image generation. These hands-on experiences will deepen your understanding of using FastAPI in real-world scenarios. By the end of this book, you'll be well equipped to maintain, design, and monitor applications to meet the highest programming standards using FastAPI, empowering you to create fast and reliable data science API backends with ease while keeping up with the latest advancements.
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Jul 2023 422 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author François Voron
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eBook $39.99
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Python – Complete Python, Django, Data Science and ML Guide
Python – Complete Python, Django, Data Science and ML Guide
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Nov 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (4)
Video 50hrs 30mins
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (4)
Dive into Programming, Django, Jupyter, Pygame, and AI Essentials
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Video Video
$129.99
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Python – Complete Python, Django, Data Science and ML Guide
Dive into Programming, Django, Jupyter, Pygame, and AI Essentials
Description
Join us on an immersive Python programming journey, spanning over 50 hours of learning. Whether you're a novice or experienced, this course equips you with vital Python skills for careers and projects. Starting from the basics, grasp Python's core principles and proficiency in real-world functions. As Python's popularity grows, this course readies you for the rising demand for Python developers. You'll practice hand-on examples using Python's interpreter and Visual Studio Code with Code Runner to solidify your skills. With a focus on Data Science and Machine Learning, you'll master essential packages such as NumPy, Pandas, Matplotlib, and Scikit-learn, using the versatile Jupyter Notebook. The course extensively covers Python's fundamental aspects, spanning variables, lists, dictionaries, and venturing into advanced topics like classes, loops, modules, and creating virtual environments. The goal is to provide you with a solid Python foundation. You'll also gain insight into functional and object-oriented Python programming, making you a versatile coder. The course is thoughtfully structured, explaining not just "how" but also "why" we use specific methods and best practices. By course end, you'll harness Python's full potential for web and mobile app development, data science, machine learning, and game creation.
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50hrs 30mins
Published : Nov 2023
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Bogdan Stashchuk
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Video $129.99
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Data Science for Web3
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Data Science for Web3
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Dec 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (3)
Paperback 344 pages
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (3)
A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases
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  • 9781837635580 eBook $35.99
  • 9781837637546 Paperback $44.99
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Data Science for Web3
A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases
Description
Data is the new oil and Web3 is generating it at an unprecedented rate. Complete with practical examples, detailed explanations, and ideas for portfolio development, this comprehensive book serves as a step-by-step guide covering the industry best practices, tools, and resources needed to easily navigate the world of data in Web3. You’ll begin by acquiring a solid understanding of key blockchain concepts and the fundamental data science tools essential for Web3 projects. The subsequent chapters will help you explore the main data sources that can help address industry challenges, decode smart contracts, and build DeFi- and NFT-specific datasets. You’ll then tackle the complexities of feature engineering specific to blockchain data and familiarize yourself with diverse machine learning use cases that leverage Web3 data. The book includes interviews with industry leaders providing insights into their professional journeys to drive innovation in the Web 3 environment. Equipped with experience in handling crypto data, you’ll be able to demonstrate your skills in job interviews, academic pursuits, or when engaging potential clients. By the end of this book, you’ll have the essential tools to undertake end-to-end data science projects utilizing blockchain data, empowering you to help shape the next-generation internet.
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Dec 2023 344 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Gabriela Castillo Areco
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Data Science Projects with Python
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Data Science Projects with Python
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Jul 2021
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (60)
Paperback 432 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (60)
A case study approach to gaining valuable insights from real data with machine learning
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  • 9781800569447 eBook $26.99
  • 9781800564480 Paperback $38.99
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Data Science Projects with Python
A case study approach to gaining valuable insights from real data with machine learning
Description
If data is the new oil, then machine learning is the drill. As companies gain access to ever-increasing quantities of raw data, the ability to deliver state-of-the-art predictive models that support business decision-making becomes more and more valuable. In this book, you’ll work on an end-to-end project based around a realistic data set and split up into bite-sized practical exercises. This creates a case-study approach that simulates the working conditions you’ll experience in real-world data science projects. You’ll learn how to use key Python packages, including pandas, Matplotlib, and scikit-learn, and master the process of data exploration and data processing, before moving on to fitting, evaluating, and tuning algorithms such as regularized logistic regression and random forest. Now in its second edition, this book will take you through the end-to-end process of exploring data and delivering machine learning models. Updated for 2021, this edition includes brand new content on XGBoost, SHAP values, algorithmic fairness, and the ethical concerns of deploying a model in the real world. By the end of this data science book, you’ll have the skills, understanding, and confidence to build your own machine learning models and gain insights from real data.
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Jul 2021 432 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Stephen Klosterman
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Graph Data Science with Neo4j
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Graph Data Science with Neo4j
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Jan 2023
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (6)
Paperback 288 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (6)
Learn how to use Neo4j 5 with Graph Data Science library 2.0 and its Python driver for your project
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  • 9781804614907 eBook $37.99
  • 9781804612743 Paperback $46.99
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Graph Data Science with Neo4j
Learn how to use Neo4j 5 with Graph Data Science library 2.0 and its Python driver for your project
Description
Neo4j, along with its Graph Data Science (GDS) library, is a complete solution to store, query, and analyze graph data. As graph databases are getting more popular among developers, data scientists are likely to face such databases in their career, making it an indispensable skill to work with graph algorithms for extracting context information and improving the overall model prediction performance. Data scientists working with Python will be able to put their knowledge to work with this practical guide to Neo4j and the GDS library that offers step-by-step explanations of essential concepts and practical instructions for implementing data science techniques on graph data using the latest Neo4j version 5 and its associated libraries. You’ll start by querying Neo4j with Cypher and learn how to characterize graph datasets. As you get the hang of running graph algorithms on graph data stored into Neo4j, you’ll understand the new and advanced capabilities of the GDS library that enable you to make predictions and write data science pipelines. Using the newly released GDSL Python driver, you’ll be able to integrate graph algorithms into your ML pipeline. By the end of this book, you’ll be able to take advantage of the relationships in your dataset to improve your current model and make other types of elaborate predictions.
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Jan 2023 288 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Scifo
Author Estelle Scifo
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eBook $37.99
Paperback $46.99
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Building Data Science Applications with FastAPI
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
AI Assistant
Building Data Science Applications with FastAPI
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Oct 2021
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (16)
Paperback 426 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (16)
Develop, manage, and deploy efficient machine learning applications with Python
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Paperback eBook
  • 9781801074186 eBook $43.99
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Building Data Science Applications with FastAPI
Develop, manage, and deploy efficient machine learning applications with Python
Description
FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you’ll be able to create fast and reliable data science API backends using practical examples. This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you’ll cover best practices relating to testing and deployment to run a high-quality and robust application. You’ll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you’ll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you’ll see how to implement a real-time face detection system using WebSockets and a web browser as a client. By the end of this FastAPI book, you’ll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI.
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Oct 2021 426 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Voron
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Principles of Data Science
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Principles of Data Science
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Dec 2016
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.9 (8)
Paperback 388 pages
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.9 (8)
Mathematical techniques and theory to succeed in data-driven industries
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  • 9781785888922 eBook $39.99
  • 9781785887918 Paperback $48.99
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Principles of Data Science
Mathematical techniques and theory to succeed in data-driven industries
Description
Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you’ll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas. With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you’ll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You’ll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means.
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Dec 2016 388 pages
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Statistics and Mathematics for Data Science and Data Analytics
Statistics and Mathematics for Data Science and Data Analytics
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Jan 2023
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Explore statistics and probability to extensively understand data science and business analysis!
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Statistics and Mathematics for Data Science and Data Analytics
Explore statistics and probability to extensively understand data science and business analysis!
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If you aim for a career in data science or data analytics, this course will equip you with the practical knowledge needed to master basic statistics. You need good statistics and probability theory knowledge to become a data scientist or analyst. The course begins with an introduction to descriptive statistics and explains the basics, including the mean, median, mode, and skewness. You will then learn more about ranges, interquartile range (IQR), samples and populations, variance, and standard deviation. The following section will explain distributions in detail, including normal distribution and Z-scores. Then, you will explore probability in detail, go over the Bayes theorem, the Central Limit theorem, the law of large numbers, and finally, Poisson’s distribution. Next, you will comprehensively explore linear regression and the coefficients of regression, mean square error, mean absolute error, and root mean square error. You will also explore hypothesis testing and type I and II errors in more detail and then learn comprehensively about the analysis of variance (ANOVA). After completing this course, you will comprehensively acquire knowledge about statistical fundamentals, data analysis methods, decision-making processes, and machine learning concepts with examples. All resources are available at: https://github.com/PacktPublishing/Statistics-Mathematics-for-Data-Science-Data-Analytics
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11hrs 22mins
Published : Jan 2023
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Author Nikolai Schuler
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Beginning Data Science with Python and Jupyter
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Beginning Data Science with Python and Jupyter
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Jun 2018
Full star icon Full star icon Full star icon Full star icon Empty star icon 4 (5)
Paperback 194 pages
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Use powerful industry-standard tools within Jupyter and the Python ecosystem to unlock new, actionable insights from your data
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  • 9781789534658 eBook $13.99
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Beginning Data Science with Python and Jupyter
Use powerful industry-standard tools within Jupyter and the Python ecosystem to unlock new, actionable insights from your data
Description
Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context.
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Jun 2018 194 pages
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Author Galea
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The Data Science Workshop
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The Data Science Workshop
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Jan 2020
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.3 (4)
Paperback 818 pages
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A New, Interactive Approach to Learning Data Science
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  • 9781838983086 eBook $29.99
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The Data Science Workshop
A New, Interactive Approach to Learning Data Science
Description
You already know you want to learn data science, and a smarter way to learn data science is to learn by doing. The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. You'll learn from real examples that lead to real results. Throughout The Data Science Workshop, you'll take an engaging step-by-step approach to understanding data science. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Data Science Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your data science book. Fast-paced and direct, The Data Science Workshop is the ideal companion for data science beginners. You'll learn about machine learning algorithms like a data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.
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Jan 2020 818 pages
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Author Anthony So
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Building Data Science Solutions with Anaconda
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Building Data Science Solutions with Anaconda
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May 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (12)
Paperback 330 pages
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A comprehensive starter guide to building robust and complete models
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  • 9781800561564 eBook $37.99
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Building Data Science Solutions with Anaconda
A comprehensive starter guide to building robust and complete models
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You might already know that there's a wealth of data science and machine learning resources available on the market, but what you might not know is how much is left out by most of these AI resources. This book not only covers everything you need to know about algorithm families but also ensures that you become an expert in everything, from the critical aspects of avoiding bias in data to model interpretability, which have now become must-have skills. In this book, you'll learn how using Anaconda as the easy button, can give you a complete view of the capabilities of tools such as conda, which includes how to specify new channels to pull in any package you want as well as discovering new open source tools at your disposal. You’ll also get a clear picture of how to evaluate which model to train and identify when they have become unusable due to drift. Finally, you’ll learn about the powerful yet simple techniques that you can use to explain how your model works. By the end of this book, you’ll feel confident using conda and Anaconda Navigator to manage dependencies and gain a thorough understanding of the end-to-end data science workflow.
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May 2022
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330 pages
AI Assistant AI Assistant
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Author Meador
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Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python
Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python
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Feb 2023
Video 4hrs 21mins
Get ready for AI, ML, and DL with NumPy, SciPy, Pandas, and Matplotlib stack
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Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python
Get ready for AI, ML, and DL with NumPy, SciPy, Pandas, and Matplotlib stack
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Welcome to the course where you will learn about the NumPy stack in Python, which is an important prerequisite for deep learning, machine learning, and data science. In this self-paced course, you will learn how to use NumPy, Matplotlib, Pandas, and SciPy to perform critical tasks related to data science and machine learning. This involves performing numerical computation and representing data, visualizing data with plots, loading in, and manipulating data using DataFrames, performing statistics and probability, and building machine learning models for classification and regression. In this course, we will first start with NumPy; we will understand the benefits of NumPy array and then we will look at some complicated matrix operations, such as products, inverses, determinants, and solving linear systems. Then we will cover Matplotlib. In this section, we will go over some common plots, namely the line chart, scatter plot, and histogram. We will also look at how to show images using Matplotlib. Next, we will talk about Pandas. We will look at how much easier it is to load a dataset using Pandas versus trying to do it manually. Then we will look at some data frame operations useful in machine learning, such as filtering by column, filtering by row, and the apply function. Later, you will learn about SciPy. In this section, you will learn how to do common statistics calculations, including getting the PDF value, the CDF value, sampling from a distribution, and statistical testing. Finally, we will also cover some basics of machine learning that will help us start our deep learning journey. By the end of the course, we will be able to confidently use the NumPy stack in deep learning and data science.
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4hrs 21mins
Published : Feb 2023
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Lazy Programmer
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Cleaning Data for Effective Data Science
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Cleaning Data for Effective Data Science
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Mar 2021
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (18)
Paperback 498 pages
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Doing the other 80% of the work with Python, R, and command-line tools
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  • 9781801074407 eBook $29.99
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Cleaning Data for Effective Data Science
Doing the other 80% of the work with Python, R, and command-line tools
Description
Data cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way. In a light-hearted and engaging exploration of different tools, techniques, and datasets real and fictitious, Python veteran David Mertz teaches you the ins and outs of data preparation and the essential questions you should be asking of every piece of data you work with. Using a mixture of Python, R, and common command-line tools, Cleaning Data for Effective Data Science follows the data cleaning pipeline from start to end, focusing on helping you understand the principles underlying each step of the process. You'll look at data ingestion of a vast range of tabular, hierarchical, and other data formats, impute missing values, detect unreliable data and statistical anomalies, and generate synthetic features. The long-form exercises at the end of each chapter let you get hands-on with the skills you've acquired along the way, also providing a valuable resource for academic courses.
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Mar 2021 498 pages
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Author David Mertz
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Data Science for Marketing Analytics
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Data Science for Marketing Analytics
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Sep 2021
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3 (203)
Paperback 636 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3 (203)
A practical guide to forming a killer marketing strategy through data analysis with Python
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  • 9781800563889 eBook $29.99
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Data Science for Marketing Analytics
A practical guide to forming a killer marketing strategy through data analysis with Python
Description
Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making.
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Sep 2021 636 pages
AI Assistant AI Assistant
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Author Mirza Rahim Baig
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Data Science Algorithms in a Week
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Data Science Algorithms in a Week
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Oct 2018
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7 (3)
Paperback 214 pages
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Top 7 algorithms for scientific computing, data analysis, and machine learning
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  • 9781789800968 eBook $35.99
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Data Science Algorithms in a Week
Top 7 algorithms for scientific computing, data analysis, and machine learning
Description
Machine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed. Through algorithmic and statistical analysis, these models can be leveraged to gain new knowledge from existing data as well. Data Science Algorithms in a Week addresses all problems related to accurate and efficient data classification and prediction. Over the course of seven days, you will be introduced to seven algorithms, along with exercises that will help you understand different aspects of machine learning. You will see how to pre-cluster your data to optimize and classify it for large datasets. This book also guides you in predicting data based on existing trends in your dataset. This book covers algorithms such as k-nearest neighbors, Naive Bayes, decision trees, random forest, k-means, regression, and time-series analysis. By the end of this book, you will understand how to choose machine learning algorithms for clustering, classification, and regression and know which is best suited for your problem
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Oct 2018 214 pages
AI Assistant AI Assistant
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Author David Toth
Author Natingga
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Statistics for Data Science
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Statistics for Data Science
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Nov 2017
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.6 (5)
Paperback 286 pages
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Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks
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  • 9781788295345 eBook $35.99
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Statistics for Data Science
Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks
Description
Data science is an ever-evolving field, which is growing in popularity at an exponential rate. Data science includes techniques and theories extracted from the fields of statistics; computer science, and, most importantly, machine learning, databases, data visualization, and so on. This book takes you through an entire journey of statistics, from knowing very little to becoming comfortable in using various statistical methods for data science tasks. It starts off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for statistical computation are clearly explained along with logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks. By the end of the book, you will be comfortable with performing various statistical computations for data science programmatically.
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Nov 2017 286 pages
AI Assistant AI Assistant
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Author James D. Miller
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Getting Started with Streamlit for Data Science
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Getting Started with Streamlit for Data Science
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Aug 2021
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (21)
Paperback 282 pages
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Create and deploy Streamlit web applications from scratch in Python
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  • 9781800563209 eBook $55.99
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Getting Started with Streamlit for Data Science
Create and deploy Streamlit web applications from scratch in Python
Description
Streamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time. You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps. By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.
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Aug 2021 282 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Tyler Richards
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Java for Data Science
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Java for Data Science
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Jan 2017
Paperback 386 pages
Examine the techniques and Java tools supporting the growing field of data science
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  • 9781785281242 eBook $43.99
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Java for Data Science
Examine the techniques and Java tools supporting the growing field of data science
Description
para 1: Get the lowdown on Java and explore big data analytics with Java for Data Science. Packed with examples and data science principles, this book uncovers the techniques & Java tools supporting data science and machine learning. Para 2: The stability and power of Java combines with key data science concepts for effective exploration of data. By working with Java APIs and techniques, this data science book allows you to build applications and use analysis techniques centred on machine learning. Para 3: Java for Data Science gives you the understanding you need to examine the techniques and Java tools supporting big data analytics. These Java-based approaches allow you to tackle data mining and statistical analysis in detail. Deep learning and Java data mining are also featured, so you can explore and analyse data effectively, and build intelligent applications using machine learning. para 4: What?s Inside ? Understand data science principles with Java support ? Discover machine learning and deep learning essentials ? Explore data science problems with Java-based solutions
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Jan 2017 386 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Richard M. Reese
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Hands-On Data Science with Anaconda
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Hands-On Data Science with Anaconda
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May 2018
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.6 (5)
Paperback 364 pages
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.6 (5)
Utilize the right mix of tools to create high-performance data science applications
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  • 9781788834735 eBook $29.99
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Hands-On Data Science with Anaconda
Utilize the right mix of tools to create high-performance data science applications
Description
Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R.
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May 2018 364 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Yuxing Yan
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The Applied Data Science Workshop
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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The Applied Data Science Workshop
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Jul 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1)
Paperback 352 pages
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Get started with the applications of data science and techniques to explore and assess data effectively
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  • 9781800207004 eBook $26.99
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The Applied Data Science Workshop
Get started with the applications of data science and techniques to explore and assess data effectively
Description
From banking and manufacturing through to education and entertainment, using data science for business has revolutionized almost every sector in the modern world. It has an important role to play in everything from app development to network security. Taking an interactive approach to learning the fundamentals, this book is ideal for beginners. You’ll learn all the best practices and techniques for applying data science in the context of real-world scenarios and examples. Starting with an introduction to data science and machine learning, you’ll start by getting to grips with Jupyter functionality and features. You’ll use Python libraries like sci-kit learn, pandas, Matplotlib, and Seaborn to perform data analysis and data preprocessing on real-world datasets from within your own Jupyter environment. Progressing through the chapters, you’ll train classification models using sci-kit learn, and assess model performance using advanced validation techniques. Towards the end, you’ll use Jupyter Notebooks to document your research, build stakeholder reports, and even analyze web performance data. By the end of The Applied Data Science Workshop, you’ll be prepared to progress from being a beginner to taking your skills to the next level by confidently applying data science techniques and tools to real-world projects.
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Jul 2020 352 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Galea
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Mastering Java for Data Science
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Mastering Java for Data Science
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Apr 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1)
Paperback 364 pages
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Analytics and more for production-ready applications
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  • 9781785887390 eBook $43.99
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Mastering Java for Data Science
Analytics and more for production-ready applications
Description
Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings.
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Apr 2017 364 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Alexey Grigorev
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Applied Data Science with Python and Jupyter
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Applied Data Science with Python and Jupyter
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Oct 2018
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3 (3)
Paperback 192 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3 (3)
Use powerful industry-standard tools to unlock new, actionable insights from your data
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  • 9781789951929 eBook $25.99
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Applied Data Science with Python and Jupyter
Use powerful industry-standard tools to unlock new, actionable insights from your data
Description
Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations.
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Oct 2018 192 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Galea
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Hands-On Data Science for Marketing
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Hands-On Data Science for Marketing
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Mar 2019
Full star icon Full star icon Full star icon Full star icon Half star icon 4.1 (14)
Paperback 464 pages
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Improve your marketing strategies with machine learning using Python and R
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  • 9781789348828 eBook $35.99
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Hands-On Data Science for Marketing
Improve your marketing strategies with machine learning using Python and R
Description
Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies. This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R. By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business.
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Mar 2019 464 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Yoon Hyup Hwang
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Data Science, Analytics, and AI for Business and the Real World™
Data Science, Analytics, and AI for Business and the Real World™
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Mar 2022
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Video 30hrs 50mins
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Use data science and statistics to solve and gain insights into real-world problems with 35+ case studies
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$134.99
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Data Science, Analytics, and AI for Business and the Real World™
Use data science and statistics to solve and gain insights into real-world problems with 35+ case studies
Description
Right now, despite the Covid-19 economic contraction, traditional businesses are hiring data scientists in droves! Therefore, data scientist has become the top job in the U.S. for the last four years running. However, data science has a difficult learning curve. This course seeks to fill all those gaps and has a comprehensive syllabus that tackles all the major components of data science knowledge. You will be using data science to solve common business problems throughout this course. You will start with the basics of Python, Pandas, Scikit-learn, NumPy, Keras, Prophet, statsmod, SciPy, and more. You will learn statistics and probability for data science in detail. Then, you will learn visualization theory for data science and analytics using Seaborn, Matplotlib, and Plotly. You will look at dashboard design using Google Data Studio along with machine learning and deep learning theory/tools. Then, you will be solving problems using predictive modeling, classification, and deep learning. After this, you will move your focus to data analysis and statistical case studies, data science in marketing, and data science in retail. Finally, you will see deployment to the cloud using Heroku to build a machine learning API. By the end of this course, you will learn all the major components of data science and gain the confidence to enter the world of data science. All the code files and the resource files are uploaded on the GitHub repository at https://github.com/PacktPublishing/Data-Science-Analytics-AI-for-Business-the-Real-World-
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30hrs 50mins
Published : Mar 2022
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Rajeev Ratan
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Video $134.99
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Apache Spark for Data Science Cookbook
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
AI Assistant
Apache Spark for Data Science Cookbook
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Dec 2016
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Paperback 392 pages
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Solve real-world analytical problems
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Paperback eBook
  • 9781785288807 eBook $39.99
  • 9781785880100 Paperback $48.99
$39.99
$48.99
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Apache Spark for Data Science Cookbook
Solve real-world analytical problems
Description
Spark has emerged as the most promising big data analytics engine for data science professionals. The true power and value of Apache Spark lies in its ability to execute data science tasks with speed and accuracy. Spark’s selling point is that it combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. It lets you tackle the complexities that come with raw unstructured data sets with ease. This guide will get you comfortable and confident performing data science tasks with Spark. You will learn about implementations including distributed deep learning, numerical computing, and scalable machine learning. You will be shown effective solutions to problematic concepts in data science using Spark’s data science libraries such as MLLib, Pandas, NumPy, SciPy, and more. These simple and efficient recipes will show you how to implement algorithms and optimize your work.
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Dec 2016 392 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Chitturi
Author Nagamallikarjuna Inelu
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Practical Data Science Using Python
Practical Data Science Using Python
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Aug 2022
Video 29hrs 46mins
Apply Data Science Using Python, Statistical Techniques, EDA, NumPy, Pandas, Scikit Learn, and Statsmodel Libraries
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$54.99
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Practical Data Science Using Python
Apply Data Science Using Python, Statistical Techniques, EDA, NumPy, Pandas, Scikit Learn, and Statsmodel Libraries
Description
In this course, you will learn about core concepts of data science, exploratory data analysis, statistical methods, role of data, Python language, challenges of bias, variance and overfitting, choosing the right performance metrics, model evaluation techniques, model optimization using hyperparameter tuning and grid search cross validation techniques, and more. You will learn how to perform detailed data analysis using Python, statistical techniques, and exploratory data analysis, using various predictive modeling techniques such as a range of classification algorithms, regression models, and clustering models. You will learn the scenarios and use cases of deploying predictive models. This course also covers classification using decision trees, which include the Gini index and entropy measures and hyperparameter tuning. It covers the use of NumPy and Pandas libraries extensively for teaching exploratory data analysis. In addition, you will also explore advanced classification techniques and support vector machine predictions. There is also an introductory lesson included on Deep Neural Networks with a worked-out example on image classification using TensorFlow and Keras. By the end of the course, you will learn some basic foundations of data science using Python. All resources and code files are placed here: https://github.com/PacktPublishing/Practical-Data-Science-using-Python
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29hrs 46mins
Published : Aug 2022
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Manas Dasgupta
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Video $54.99
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Jupyter Notebook for Data Science
Jupyter Notebook for Data Science
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Aug 2018
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Video 3hrs 11mins
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Collaborate, create interactive visualizations, and manipulate big data in the language of your choice.
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$137.99
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Jupyter Notebook for Data Science
Collaborate, create interactive visualizations, and manipulate big data in the language of your choice.
Description
This video course will help you get familiar with Jupyter Notebook and all of its features to perform various data science tasks in Python. Jupyter Notebook is a powerful tool for interactive data exploration and visualization and has become the standard tool among data scientists. In the course, we will start from basic data analysis tasks in Jupyter Notebook and work our way up to learn some common scientific Python tools such as pandas, matplotlib, and plotly. We will work with real datasets, such as crime and traffic accidents in New York City, to explore common issues such as data scraping and cleaning. We will create insightful visualizations, showing time-stamped and spatial data. By the end of the course, you will feel confident about approaching a new dataset, cleaning it up, exploring it, and analyzing it in Jupyter Notebook to extract useful information in the form of interactive reports and information-dense data visualizations. All the code and supporting files for this course are available on GitHub at https://github.com/PacktPublishing/Jupyter-Notebook-for-Data-Science This course uses Jupyter 5.4.1, while not the latest version available, it provides relevant and informative content for data science enthusiasts.
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3hrs 11mins
Published : Aug 2018
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Drazen Lucanin
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Video $137.99
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Machine Learning, Data Science and Generative AI with Python
Machine Learning, Data Science and Generative AI with Python
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Nov 2023
Video 18hrs 11mins
Comprehensive tutorial on machine learning, data science, TensorFlow, AI, and neural networks
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Video Video
$99.99
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Machine Learning, Data Science and Generative AI with Python
Comprehensive tutorial on machine learning, data science, TensorFlow, AI, and neural networks
Description
This course begins with a Python crash course and then guides you on setting up Microsoft Windows-based PCs, Linux desktops, and Macs. After the setup, we delve into machine learning, AI, and data mining techniques, which include deep learning and neural networks with TensorFlow and Keras; generative models with variational autoencoders and generative adversarial networks; data visualization in Python with Matplotlib and Seaborn; transfer learning, sentiment analysis, image recognition, and classification; regression analysis, K-Means Clustering, Principal Component Analysis, training/testing and cross-validation, Bayesian methods, decision trees, and random forests. Additionally, we will cover multiple regression, multilevel models, support vector machines, reinforcement learning, collaborative filtering, K-Nearest Neighbors, the bias/variance tradeoff, ensemble learning, term frequency/inverse document frequency, experimental design, and A/B testing, feature engineering, hyperparameter tuning, and much more! There's a dedicated section on machine learning with Apache Spark to scale up these techniques to "big data" analyzed on a computing cluster. The course will cover the Transformer architecture, delve into the role of self-attention in AI, explore GPT applications, and practice fine-tuning Transformers for tasks such as movie review analysis. Furthermore, we will look at integrating the OpenAI API for ChatGPT, creating with DALL-E, understanding embeddings, and leveraging audio-to-text to enhance AI with real-world data and moderation.
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18hrs 11mins
Last Updated : Nov 2023 Published : Sep 2016
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Frank Kane
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Video $99.99
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Learn Python by Building Data Science Applications
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
AI Assistant
Learn Python by Building Data Science Applications
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Aug 2019
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Paperback 482 pages
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A fun, project-based guide to learning Python 3 while building real-world apps
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Paperback eBook
  • 9781789533064 eBook $26.99
  • 9781789535365 Paperback $38.99
$26.99
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Learn Python by Building Data Science Applications
A fun, project-based guide to learning Python 3 while building real-world apps
Description
Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards.
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Aug 2019
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482 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Kats
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Paperback $38.99
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