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

View More author details

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

An introduction to machine learning

In this first section, we will kick off our machine learning journey with a brief introduction to machine learning, why we need it, how it differs from automation, and how it improves our lives.

Machine learning is a term that was coined around 1960, consisting of two words—machine, which corresponds to a computer, robot, or other device, and learning, which refers to an activity intended to acquire or discover event patterns, which we humans are good at. Interesting examples include facial recognition, translation, responding to emails, and making data-driven business decisions. You will see many more examples throughout this book.

Understanding why we need machine learning

Why do we need machine learning and why do we want a machine to learn the same way as a human? We can look at it from three main perspectives: maintenance, risk mitigation, and advantages.

First and foremost, of course, computers and robots...