You're reading from Python Machine Learning Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2

Product type Paperback

Published in Dec 2019

Publisher Packt

ISBN-13 9781789955750

Length 772 pages

Edition 3rd Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Authors (2):

Vahid Mirjalili

Sebastian Raschka

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Table of Contents (21) Chapters

Preface

1. Giving Computers the Ability to Learn from Data FREE CHAPTER

2. Training Simple Machine Learning Algorithms for Classification

3. A Tour of Machine Learning Classifiers Using scikit-learn

4. Building Good Training Datasets – Data Preprocessing

5. Compressing Data via Dimensionality Reduction

6. Learning Best Practices for Model Evaluation and Hyperparameter Tuning

7. Combining Different Models for Ensemble Learning

8. Applying Machine Learning to Sentiment Analysis

9. Embedding a Machine Learning Model into a Web Application

10. Predicting Continuous Target Variables with Regression Analysis

11. Working with Unlabeled Data – Clustering Analysis

12. Implementing a Multilayer Artificial Neural Network from Scratch

13. Parallelizing Neural Network Training with TensorFlow

14. Going Deeper – The Mechanics of TensorFlow

15. Classifying Images with Deep Convolutional Neural Networks

16. Modeling Sequential Data Using Recurrent Neural Networks

17. Generative Adversarial Networks for Synthesizing New Data

18. Reinforcement Learning for Decision Making in Complex Environments

19. Other Books You May Enjoy

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20. Index

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