You're reading from Python Machine Learning by Example Build intelligent systems using Python, TensorFlow 2, PyTorch, and scikit-learn

Product type Paperback

Published in Oct 2020

Publisher Packt

ISBN-13 9781800209718

Length 526 pages

Edition 3rd Edition

Languages

Python

Tools

PyTorch

Concepts

Machine Learning

Author (1):

Yuxi (Hayden) Liu

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Table of Contents (17) Chapters

Preface

1. Getting Started with Machine Learning and Python

2. Building a Movie Recommendation Engine with Naïve Bayes FREE CHAPTER

3. Recognizing Faces with Support Vector Machine

4. Predicting Online Ad Click-Through with Tree-Based Algorithms

5. Predicting Online Ad Click-Through with Logistic Regression

6. Scaling Up Prediction to Terabyte Click Logs

7. Predicting Stock Prices with Regression Algorithms

8. Predicting Stock Prices with Artificial Neural Networks

9. Mining the 20 Newsgroups Dataset with Text Analysis Techniques

10. Discovering Underlying Topics in the Newsgroups Dataset with Clustering and Topic Modeling

11. Machine Learning Best Practices

12. Categorizing Images of Clothing with Convolutional Neural Networks

13. Making Predictions with Sequences Using Recurrent Neural Networks

14. Making Decisions in Complex Environments with Reinforcement Learning

15. Other Books You May Enjoy

16. Index

Installing software and setting up

As the book title says, Python is the language we will use to implement all machine learning algorithms and techniques throughout the entire book. We will also exploit many popular Python packages and tools such as NumPy, SciPy, TensorFlow, and scikit-learn. By the end of this kick-off chapter, make sure you set up the tools and working environment properly, even if you are already an expert in Python or might be familiar with some of those tools.

Setting up Python and environments

We will be using Python 3 in this book. As you may know, Python 2 will no longer be supported after 2020, so starting with or switching to Python 3 is strongly recommended. Trust me, the transition is pretty smooth. But if you're stuck with Python 2, you still should be able to modify the codes to work for you. The Anaconda Python 3 distribution is one of the best options for data science and machine learning practitioners.

Anaconda is a free...