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Python Machine Learning by Example

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

Index

Symbols

A

actions 453, 454

action-value 473

activation function 256

activation functions

linear 268

ReLU 268

sigmoid 268

softmax 268

tanh 268

ad click-through

predicting, with logistic regression 165, 166

ad click-through prediction 110

with decision tree 134, 136, 137, 138, 139, 140

adjusted R² 245

agent 453, 454

AI-based assistance 4

AI plus human intelligence 4

AlphaGo 3

Anaconda 38

reference link 37

Apache Hadoop

URL 355

Arcene Dataset 97

area under the curve (AUC) 68

Artificial General Intelligence (AGI) 452

Artificial Intelligence (AI) 8

artificial masterpieces, Google Arts & Culture

reference link 261

artificial neural networks (ANNs) 11, 254

association 315

attributes 315

automation

versus machine learning 5

averaging 32

B

backpropagation 258, 259

Backpropagation Through Time (BPTT) 420

bagging 32, 140...

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Authors (1)

Yuxi (Hayden) Liu

Yuxi (Hayden) Liu

Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.

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