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Author: rasbt

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+The MIT License (MIT)
+
+Copyright (c) 2019 SEBASTIAN RASCHKA ([email protected])
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

LICENSE.txt

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+## Python Machine Learning (3rd Ed.) Code Repository
+
+![Python 3.6](https://img.shields.io/badge/Python-3.7-blue.svg)
+![License](https://img.shields.io/badge/Code%20License-MIT-blue.svg)
+
+Code repositories for the 1st and 2nd edition are available at
+
+- https://github.com/rasbt/python-machine-learning-book and
+- https://github.com/rasbt/python-machine-learning-book-2nd-edition
+
+**Python Machine Learning, 3rd Ed.**  
+
+to be published December 9th, 2019
+
+Paperback: 748 pages  
+Publisher: Packt Publishing  
+Language: English
+
+ISBN-10: 1789955750   
+ISBN-13: 978-1789955750  
+Kindle ASIN: B07VBLX2W7 
+
+[<img src="./.other/cover_1.jpg" width="248">](https://www.amazon.com/Python-Machine-Learning-scikit-learn-TensorFlow/dp/1789955750/)
+
+
+## Links
+
+- [Amazon Page](https://www.amazon.com/Python-Machine-Learning-scikit-learn-TensorFlow/dp/1789955750/)
+- [Packt Page](https://www.packtpub.com/data/python-machine-learning-third-edition)
+
+
+
+## Table of Contents and Code Notebooks
+
+**Helpful installation and setup instructions can be found in the [README.md file of Chapter 1](ch01/README.md)**
+
+**Please note that these are just the code examples accompanying the book, which we uploaded for your convenience; be aware that these notebooks may not be useful without the formulae and descriptive text.**   
+
+
+1. Machine Learning - Giving Computers the Ability to Learn from Data [[open dir](ch01)] 
+2. Training Machine Learning Algorithms for Classification [[open dir](ch02)] 
+3. A Tour of Machine Learning Classifiers Using Scikit-Learn [[open dir](ch03)] 
+4. Building Good Training Sets – Data Pre-Processing [[open dir](ch04)] 
+5. Compressing Data via Dimensionality Reduction [[open dir](ch05)] 
+6. Learning Best Practices for Model Evaluation and Hyperparameter Optimization [[open dir](ch06)]
+7. Combining Different Models for Ensemble Learning [[open dir](ch07)] 
+8. Applying Machine Learning to Sentiment Analysis [[open dir](ch08)] 
+9. Embedding a Machine Learning Model into a Web Application [[open dir](ch09)]  
+10. Predicting Continuous Target Variables with Regression Analysis [[open dir](ch10)] 
+11. Working with Unlabeled Data – Clustering Analysis [[open dir](ch11)] 
+12. Implementing a Multi-layer Artificial Neural Network from Scratch [[open dir](ch12)] 
+13. Parallelizing Neural Network Training with TensorFlow [[open dir](ch13)] 
+14. Going Deeper: The Mechanics of TensorFlow [[open dir](ch14)] 
+15. Classifying Images with Deep Convolutional Neural Networks [[open dir](ch15)]  
+16. Modeling Sequential Data Using Recurrent Neural Networks [[open dir](ch16)] 
+17. Generative Adversarial Networks for Synthesizing New Data [[open dir](ch17)]  
+18. Reinforcement Learning for Decision Making in Complex Environments [[open dir](ch18)] 
+
+
+--- 
+
+<br>
+<br>
+
+Raschka, Sebastian, and Vahid Mirjalili. *Python Machine Learning, 3rd Ed*. Packt Publishing, 2019.
+
+    @book{RaschkaMirjalili2019,  
+    address = {Birmingham, UK},  
+    author = {Raschka, Sebastian and Mirjalili, Vahid},  
+    edition = {3},  
+    isbn = {978-1789955750},   
+    publisher = {Packt Publishing},  
+    title = {{Python Machine Learning, 3rd Ed.}},  
+    year = {2019}  
+    }