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Author: fchollet

README.md

@@ -9,27 +9,27 @@ These notebooks use Python 3.7 and Keras 2.0.8. They were generated on a p2.xlar
 
 ## Table of contents
 
-* [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 2: The mathematical building blocks of neural networks](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter02_mathematical-building-blocks.ipynb)
+* [Chapter 3: Introduction to Keras and TensorFlow](https://colab.research.google.com/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](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter04_getting-started-with-neural-networks.ipynb)
+* [Chapter 5: Fundamentals of machine learning](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter05_fundamentals-of-ml.ipynb)
+* [Chapter 7: Working with Keras: a deep dive](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter07_working-with-keras.ipynb)
+* [Chapter 8: Introduction to deep learning for computer vision](https://colab.research.google.com/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)
+    - [Part 1: Image segmentation](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter09_part01_image-segmentation.ipynb)
+    - [Part 2: Modern convnet architecture patterns](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter09_part02_modern-convnet-architecture-patterns.ipynb)
+    - [Part 3: Interpreting what convnets learn](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter09_part03_interpreting-what-convnets-learn.ipynb)
+* [Chapter 10: Deep learning for timeseries](https://colab.research.google.com/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)
+    - [Part 1: Introduction](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter11_part01_introduction.ipynb)
+    - [Part 2: Sequence models](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter11_part02_sequence-models.ipynb)
+    - [Part 3: Transformer](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter11_part03_transformer.ipynb)
+    - [Part 4: Sequence-to-sequence learning](https://colab.research.google.com/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)
+    - [Part 1: Text generation](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part01_text-generation.ipynb)
+    - [Part 2: Deep Dream](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part02_deep-dream.ipynb)
+    - [Part 3: Neural style transfer](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part03_neural-style-transfer.ipynb)
+    - [Part 4: Variational autoencoders](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part04_variational-autoencoders.ipynb)
+    - [Part 5: Generative adversarial networks](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter12_part05_gans.ipynb)
+* [Chapter 13: Best practices for the real world](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter13_best-practices-for-the-real-world.ipynb)
+* [Chapter 14: Conclusions](https://colab.research.google.com/github/fchollet/deep-learning-with-python-notebooks/blob/master/chapter14_conclusions.ipynb)