Switch to 2nd edition notebooks -- let's go!

Author: fchollet

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2017 François Chollet
+Copyright (c) 2017-present François Chollet
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -1,34 +1,35 @@
 # Companion Jupyter notebooks for the book "Deep Learning with Python"
 
-This repository contains Jupyter notebooks implementing the code samples found in the book [Deep Learning with Python (Manning Publications)](https://www.manning.com/books/deep-learning-with-python?a_aid=keras&a_bid=76564dff). Note that the original text of the book features far more content than you will find in these notebooks, in particular further explanations and figures. Here we have only included the code samples themselves and immediately related surrounding comments.
+This repository contains Jupyter notebooks implementing the code samples found in the book [Deep Learning with Python, 2nd Edition (Manning Publications)](https://www.manning.com/books/deep-learning-with-python-second-edition?a_aid=keras&a_bid=76564dff).
 
-These notebooks use Python 3.6 and Keras 2.0.8. They were generated on a p2.xlarge EC2 instance.
+For readability, these notebooks only contain runnable code blocks and section titles, and omit everything else in the book: text paragraphs, figures, and pseudocode.
+**If you want to be able to follow what's going on, I recommend reading the notebooks side by side with your copy of the book.**
+
+These notebooks use Python 3.7 and Keras 2.0.8. They were generated on a p2.xlarge EC2 instance.
 
 ## Table of contents
 
-* Chapter 2:
-    * [2.1: A first look at a neural network](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/2.1-a-first-look-at-a-neural-network.ipynb)
-* Chapter 3:
-    * [3.5: Classifying movie reviews](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/3.5-classifying-movie-reviews.ipynb)
-    * [3.6: Classifying newswires](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/3.6-classifying-newswires.ipynb)
-    * [3.7: Predicting house prices](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/3.7-predicting-house-prices.ipynb)
-* Chapter 4:
-    * [4.4: Underfitting and overfitting](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/4.4-overfitting-and-underfitting.ipynb)
-* Chapter 5:
-    * [5.1: Introduction to convnets](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/5.1-introduction-to-convnets.ipynb)
-    * [5.2: Using convnets with small datasets](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/5.2-using-convnets-with-small-datasets.ipynb)
-    * [5.3: Using a pre-trained convnet](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/5.3-using-a-pretrained-convnet.ipynb)
-    * [5.4: Visualizing what convnets learn](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/5.4-visualizing-what-convnets-learn.ipynb)
-* Chapter 6:
-    * [6.1: One-hot encoding of words or characters](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/6.1-one-hot-encoding-of-words-or-characters.ipynb)
-    * [6.1: Using word embeddings](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/6.1-using-word-embeddings.ipynb)
-    * [6.2: Understanding RNNs](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/6.2-understanding-recurrent-neural-networks.ipynb)
-    * [6.3: Advanced usage of RNNs](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/6.3-advanced-usage-of-recurrent-neural-networks.ipynb)
-    * [6.4: Sequence processing with convnets](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/6.4-sequence-processing-with-convnets.ipynb)
-* Chapter 8:
-    * [8.1: Text generation with LSTM](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/8.1-text-generation-with-lstm.ipynb)
-    * [8.2: Deep dream](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/8.2-deep-dream.ipynb)
-    * [8.3: Neural style transfer](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/8.3-neural-style-transfer.ipynb)
-    * [8.4: Generating images with VAEs](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/8.4-generating-images-with-vaes.ipynb)
-    * [8.5: Introduction to GANs](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/8.5-introduction-to-gans.ipynb
-)
+* [Chapter 2: The mathematical building blocks of neural networks](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter02_mathematical-building-blocks.ipynb)
+* [Chapter 3: Introduction to Keras and TensorFlow](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter03_introduction-to-keras-and-tf.ipynb)
+* [Chapter 4: Getting started with neural networks: classification and regression](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter04_getting-started-with-neural-networks.ipynb)
+* [Chapter 5: Fundamentals of machine learning](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter05_fundamentals-of-ml.ipynb)
+* [Chapter 7: Working with Keras: a deep dive](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter07_working-with-keras.ipynb)
+* [Chapter 8: Introduction to deep learning for computer vision](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter08_intro-to-dl-for-computer-vision.ipynb)
+* Chapter 9: Advanced deep learning for computer vision
+    - [Part 1: Image segmentation](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter09_part01_image-segmentation.ipynb)
+    - [Part 2: Modern convnet architecture patterns](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter09_part02_modern-convnet-architecture-patterns.ipynb)
+    - [Part 3: Interpreting what convnets learn](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter09_part03_interpreting-what-convnets-learn.ipynb)
+* [Chapter 10: Deep learning for timeseries](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter10_dl-for-timeseries.ipynb)
+* Chapter 11: Deep learning for text
+    - [Part 1: Introduction](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter11_part01_introduction.ipynb)
+    - [Part 2: Sequence models](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter11_part02_sequence-models.ipynb)
+    - [Part 3: Transformer](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter11_part03_transformer.ipynb)
+    - [Part 4: Sequence-to-sequence learning](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter11_part04_sequence-to-sequence-learning.ipynb)
+* Chapter 12: Generative deep learning
+    - [Part 1: Text generation](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part01_text-generation.ipynb)
+    - [Part 2: Deep Dream](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part02_deep-dream.ipynb)
+    - [Part 3: Neural style transfer](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part03_neural-style-transfer.ipynb)
+    - [Part 4: Variational autoencoders](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part04_variational-autoencoders.ipynb)
+    - [Part 5: Generative adversarial networks](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part05_gans.ipynb)
+* [Chapter 13: Best practices for the real world](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter13_best-practices-for-the-real-world.ipynb)
+* [Chapter 14: Conclusions](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter14_conclusions.ipynb)