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Python: Real-World Data Science
Python: Real-World Data Science

Python: Real-World Data Science: Real-World Data Science

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Profile Icon Robert Layton Profile Icon Phuong Vo.T.H Profile Icon Martin Czygan Profile Icon Dusty Phillips Profile Icon Fabrizio Romano Profile Icon Sebastian Raschka +2 more Show less
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Course Jun 2016 1255 pages 1st Edition
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Profile Icon Robert Layton Profile Icon Phuong Vo.T.H Profile Icon Martin Czygan Profile Icon Dusty Phillips Profile Icon Fabrizio Romano Profile Icon Sebastian Raschka +2 more Show less
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Course Jun 2016 1255 pages 1st Edition

Key benefits

  • Unleash the power of Python 3 objects
  • Learn to use powerful Python libraries for effective data processing and analysis
  • Harness the power of Python to analyze data and create insightful predictive models
  • Unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics

Description

The Python: Real-World Data Science course will take you on a journey to become an efficient data science practitioner by thoroughly understanding the key concepts of Python. This learning path is divided into four modules and each module are a mini course in their own right, and as you complete each one, you’ll have gained key skills and be ready for the material in the next module. The course begins with getting your Python fundamentals nailed down. After getting familiar with Python core concepts, it’s time that you dive into the field of data science. In the second module, you'll learn how to perform data analysis using Python in a practical and example-driven way. The third module will teach you how to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis to more complex data types including text, images, and graphs. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. In the final module, we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls.

Who is this book for?

Entry-level analysts who want to enter in the data science world will find this course very useful to get themselves acquainted with Python’s data science capabilities for doing real-world data analysis.

What you will learn

  • Install and setup Python
  • Implement objects in Python by creating classes and defining methods
  • Get acquainted with NumPy to use it with arrays and array-oriented computing in data analysis
  • Create effective visualizations for presenting your data using Matplotlib
  • Process and analyze data using the time series capabilities of pandas
  • Interact with different kind of database systems, such as file, disk format, Mongo, and Redis
  • Apply data mining concepts to real-world problems
  • Compute on big data, including real-time data from the Internet
  • Explore how to use different machine learning models to ask different questions of your data

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 13, 2016
Length: 1255 pages
Edition : 1st
Language : English
ISBN-13 : 9781786465160
Category :
Languages :

Product Details

Publication date : Jun 13, 2016
Length: 1255 pages
Edition : 1st
Language : English
ISBN-13 : 9781786465160
Category :
Languages :

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Table of Contents

12 Chapters
Table of Contents Chevron down icon Chevron up icon
Python: Real-World Data Science Chevron down icon Chevron up icon
Meet Your Course Guide Chevron down icon Chevron up icon
What's so cool about Data Science? Chevron down icon Chevron up icon
Course Structure Chevron down icon Chevron up icon
Course Journey Chevron down icon Chevron up icon
The Course Roadmap and Timeline Chevron down icon Chevron up icon
1. Course Module 1: Python Fundamentals Chevron down icon Chevron up icon
2. Course Module 2: Data Analysis Chevron down icon Chevron up icon
3. Course Module 3: Data Mining Chevron down icon Chevron up icon
4. Course Module 4: Machine Learning Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
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