Data

tensorflow This page features the latest and most popular books on TensorFlow, a popular open source platform for machine learning. The books cover topics like building neural networks with TensorFlow, leveraging TensorFlow for natural language processing, deploying TensorFlow models in production, and more. There are books for beginners just starting with machine learning as well as more advanced books that teach techniques like transfer learning and generative adversarial networks. Whether you want to learn the fundamentals of TensorFlow, build deep learning models, or deploy ML solutions, these books have got you covered.

Rising Stars

Recently released data books which are getting a lot of attention.

Et al.

Aug 2023 230 pages

eBook

€11.99

Generative AI with LangChain

Dec 2023 360 pages

eBook

€29.99

Mastering Tableau 2023

Aug 2023 684 pages

eBook

€29.99

Building AI Applications with ChatGPT APIs

Sep 2023 258 pages

eBook

€26.99

Data Engineering with AWS

Oct 2023 636 pages

eBook

€31.99

Modern Data Architecture on AWS

Aug 2023 420 pages

eBook

€26.99

Practical Guide to Applied Conformal Prediction in Python

Dec 2023 240 pages

eBook

€29.99

TinyML Cookbook

Nov 2023 664 pages

eBook

€26.99

Data Modeling with Microsoft Excel

Nov 2023 316 pages

eBook

€20.99

Building Statistical Models in Python

Aug 2023 420 pages

eBook

€29.99

Career Pathways

A collection of reading lists made by our expert authors to help get you your next job.

Getting Started with ChatGPT

Stay ahead of the game and start unlocking the full potential of OpenAI and ChatGPT today.

Artificial Intelligence Programming with Python

Swiftly grasp the art of building smart AI applications using Python. Learn AI basics and dive deeper into this captivating field. Develop your own smart apps with a focus on real-world cases and applying modern AI algorithms to diverse challenges.

Become a Python Data Analyst

Master cutting-edge Python techniques for managing vast volumes of unstructured data. This list guides you through essential steps like data prep, collection, wrangling, and analysis, using practical examples. Leverage Python and libraries to thoroughly depict, address, and transform data to suit your objectives.

Mastering Natural Language Processing

This list is a comprehensive guide for NLP practitioners, ML developers, and data scientists to create powerful NLP systems for complex real-world tasks. It covers a variety of NLP techniques and concepts, utilizing popular tools like Tensorflow and Transformers.

Become a Successful Data Scientist

This list provides a strong theoretical base and practical learning path to become a skilled data scientist. It includes intuitive books with working examples to deepen your Python machine learning skills. Covering essential algorithms, the books teach core machine learning principles, empowering you to create models and applications with confidence. Expert techniques and model insights are shared for fine-tuning and comprehensive understanding.

Learn Math and Statistics for Machine Learning

Master vital math and stats for computer science and machine learning with this list. It delves into complex concepts, elevating your skills. Enhance data science knowledge, extract insights, and grasp deep learning model functioning.

Power BI for Business Intelligence - Beginner to Advanced

This list empowers dynamic data utilization. Learn data modeling, analytics, and business intelligence with practical examples. Master Microsoft Power BI for interactive solutions and compelling storytelling. Develop robust models, dashboards, and advanced DAX queries for agile insights in evolving business contexts.

PyTorch Masterclass

This curated reading list empowers you to enter the world of deep learning and AI through PyTorch. You'll master PyTorch syntax, develop deep neural networks, and deploy intelligent applications. Explore over 50 real-world image applications, 35 neural network architectures, and diverse domains like music, NLP, GANs, Deep RL, and more. Gain expert insights to efficiently train large models, employ AutoML for neural architecture search, and swiftly prototype models with PyTorch and fast.ai.

The Complete TensorFlow Masterclass

Discover a curated list for mastering TensorFlow and creating potent machine learning algorithms. From building neural network applications in this robust stack to using TensorFlow in production, TF mobile, and AutoML, you'll enhance your skills. Learn advanced machine learning and deep learning techniques to improve speed and accuracy. Explore diverse application areas like image generation, GANs, computer vision, NLP, Transformers, Deep RL, and more, using TensorFlow and state-of-the-art architectures.

The Definitive Guide to Tableau

This reading list equips you with the skills to create impactful data visualizations, interactive dashboards, and leverage key insights to transform your organization. It covers data cleaning and structuring using Tableau Prep and provides hands-on exercises to prepare for the Tableau Desktop Certified Associate exam. Get ready to redefine business analytics and tackle complex data challenges.

Developing Enterprise Machine Learning Applications on the Cloud

This reading list offers a practical introduction to using popular cloud platforms like Azure, AWS, and GCP for data analytics, machine learning, and AI. Learn to build, deploy, and manage cloud-based machine learning models efficiently. It emphasizes optimizing productivity, rapid deployment, cost-effectiveness, and achieving higher model accuracy. Explore the full spectrum of ML workflows, including experimentation, training, monitoring, scaling, deployment, and automation. Additionally, discover how to design and develop edge analytics applications with Azure IoT Edge.

Machine Learning with Amazon SageMaker

This reading list is for machine learning developers, data scientists, and AWS users who are new to using Amazon SageMaker and want to build high-quality machine learning models without worrying about infrastructure. The books covered in this reading list will help you learn best practices for all phases of building machine learning solutions - from data preparation to monitoring models in production using AWS cloud.

Python for Algorithmic Trading

This reading list will help you understand the fundamentals and core techniques of algorithmic trading in financial markets using real-world examples. You will learn to apply various algorithms to market data and analyze results which will help you to build and deploy your algorithmic trading systems and strategies using Python. You will also learn how to implement machine learning algorithms to apply predictive modeling to trading decisions. Reading the books covered in this list will give you confidence to implement and safely operate algorithmic trading strategies in live markets.

Popular Authors (10)

Greg Deckler

Greg Deckler is Vice President of the Microsoft Practice at Fusion Alliance and has been a professional technology systems consultant for over 25 years. Internationally recognized as an expert in Power BI, Greg Deckler is a Microsoft MVP for Data Platform and a superuser within the Power BI community with over 100,000 messages read, more than 11,000 replies, over 2,300 answers, and more than 75 entries in the Quick Measures Gallery. Greg founded the Columbus Azure ML and Power BI User Group (CAMLPUG) and presents at numerous conferences and events, including SQL Saturday, DogFood, and the Dynamic Communities User Group/Power Platform Summit.

Most popular book of Greg Deckler

Learn Power BI

See 6 other products by Greg Deckler

Mr. Mark Price

Mark J. Price is a Microsoft Specialist: Programming in C# and Architecting Microsoft Azure Solutions, with over 20 years' experience. Since 1993, he has passed more than 80 Microsoft programming exams and specializes in preparing others to pass them. Between 2001 and 2003, Mark was employed to write official courseware for Microsoft in Redmond, USA. His team wrote the first training courses for C# while it was still an early alpha version. While with Microsoft, he taught "train-the-trainer" classes to get other MCTs up-to-speed on C# and .NET. Mark holds a Computer Science BSc. Hons. Degree.

Most popular book of Mr. Mark Price

C# 6 and .NET Core 1.0

See 10 other products by Mr. Mark Price

Dr. Sebastian Raschka

Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.

Most popular book of Dr. Sebastian Raschka

Instant Heat Maps in R How-to

See 7 other products by Dr. Sebastian Raschka

Duilio Tacconi

Duilio Tacconi is a Microsoft Dynamics NAV/Microsoft Dynamics 365 Business Central Escalation Engineer at Microsoft EMEA Customer Support & Services (CSS). He joined Microsoft in 2008 after working in a customer IT department with a focus on system administration and development. Despite graduating with the highest score in Agricultural Science in 1996, he is in the ERP circuit since 1998 as developer and system implementer for several companies with Microsoft and non-Microsoft technologies. Currently, he is a subject matter expert in EMEA for RDLC Report development and one of Microsoft EMEA CSS reference for Managed Service for Partners (MSfP). Three times IronMan finisher, Duilio lives in Cernusco Sul Naviglio (Italy) with his beloved wife Laura and his 2 years old son Leonardo.

Most popular book of Duilio Tacconi

Dynamics 365 Business Central Development Quick Start Guide

See 3 other products by Duilio Tacconi

Gabriel Baptista

Gabriel Baptista is a software architect who leads technical teams for Microsoft products across numerous projects for retail and industry. He is an Azure Platform-as-a-Service (PaaS) solutions specialist, a computing professor, a co-founder of a start-up for developing mobile applications, and also a speaker on the Channel 9 community.

Most popular book of Gabriel Baptista

Software Architecture with C# 9 and .NET 5

See 3 other products by Gabriel Baptista

Per Larsen

Per Larsen works as a Senior Program Manager for Microsoft Endpoint Manager - Customer Acceleration Team - Commercial Management Experiences (CMX) Engineering, where he takes learnings from Microsoft’s largest and most strategic customers back into the rest of engineering to drive improvements for the service so that customers have a continuously improving product experience. He also helps deploy and adopt Microsoft Endpoint Manager - Microsoft Intune. Per mainly focuses on the management of Windows and special devices such as HoloLens 2, Surface Hub, and Microsoft Teams Room System. Per was also an MVP in Enterprise Mobility, from 1st July 2016 to when he joined Microsoft on 1st April 2018.

Most popular book of Per Larsen

Mastering Microsoft Endpoint Manager

See 2 other products by Per Larsen

Carl-Hugo Marcotte

Carl-Hugo Marcotte has been developing, designing, and architecting web applications professionally since 2005, wrote his first line of code at about eight years old, and holds a bachelor's degree in computer science. After working at a firm for a few years, he became an independent consultant, where he developed projects of different sizes for SMEs and educational institutions. He is now a Senior Solutions Architect at Export Development Canada and is passionate about software architecture, C#, ASP.NET Core, and the Cloud. He loves to share his knowledge, which led him to teaching programming, blogging, and creating, maintaining and contributing to multiple open-source projects.

Most popular book of Carl-Hugo Marcotte

An Atypical ASP.NET Core 5 Design Patterns Guide

See 3 other products by Carl-Hugo Marcotte

Ben Auffarth

Ben Auffarth is a full-stack data scientist who has >15 years of work experience. With a background and Ph.D. in computational and cognitive neuroscience from one of Europe's top engineering universities, he has designed and conducted wet lab experiments on cell cultures, analyzed experiments with terabytes of data, run brain models on IBM supercomputers with up to 64k cores, built production systems processing hundreds of thousands of transactions per day, and trained neural networks on millions of text documents. In his work, he often notices a lack of appreciation for the importance of time-related factors, a deficit he wanted to address in this book. He co-founded and is the former president of Data Science Speakers, London.

Most popular book of Ben Auffarth

Artificial Intelligence with Python Cookbook

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Maaike van Putten

Maaike van Putten is an experienced software developer and Pluralsight, LinkedIn Learning, Udemy, and Bright Boost instructor. She has a passion for software development and helping others get to the next level in their career.

Most popular book of Maaike van Putten

JavaScript from Beginner to Professional

See 3 other products by Maaike van Putten

Stefan Jansen

Stefan is the founder and CEO of Applied AI. He advises Fortune 500 companies, investment firms, and startups across industries on data & AI strategy, building data science teams, and developing end-to-end machine learning solutions for a broad range of business problems. Before his current venture, he was a partner and managing director at an international investment firm, where he built the predictive analytics and investment research practice. He was also a senior executive at a global fintech company with operations in 15 markets, advised Central Banks in emerging markets, and consulted for the World Bank. He holds Master's degrees in Computer Science from Georgia Tech and in Economics from Harvard and Free University Berlin, and a CFA Charter. He has worked in six languages across Europe, Asia, and the Americas and taught data science at Datacamp and General Assembly.

Most popular book of Stefan Jansen

Hands-On Machine Learning for Algorithmic Trading

See 2 other products by Stefan Jansen

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Career Pathways

Popular Authors (10)

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