diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -8,27 +8,63 @@ These notebooks use Python 3.6 and Keras 2.0.8. They were generated on a p2.xlar
* 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)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F2.1-a-first-look-at-a-neural-network.ipynb)
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* 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)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F3.5-classifying-movie-reviews.ipynb)
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* [3.6: Classifying newswires](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/3.6-classifying-newswires.ipynb)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F3.6-classifying-newswires.ipynb)
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* [3.7: Predicting house prices](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/3.7-predicting-house-prices.ipynb)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F3.7-predicting-house-prices.ipynb)
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* 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)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F4.4-overfitting-and-underfitting.ipynb)
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* 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)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F5.1-introduction-to-convnets.ipynb)
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* [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)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F5.2-using-convnets-with-small-datasets.ipynb)
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* [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)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F5.3-using-a-pretrained-convnet.ipynb)
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* [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)
+ [
](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F5.4-visualizing-what-convnets-learn.ipynb)
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* 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)
+ [
](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F6.1-one-hot-encoding-of-words-or-characters.ipynb)
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* [6.1: Using word embeddings](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/6.1-using-word-embeddings.ipynb)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F6.1-using-word-embeddings.ipynb)
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* [6.2: Understanding RNNs](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/6.2-understanding-recurrent-neural-networks.ipynb)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F6.2-understanding-recurrent-neural-networks.ipynb)
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* [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)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F6.3-advanced-usage-of-recurrent-neural-networks.ipynb)
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* [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)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F6.4-sequence-processing-with-convnets.ipynb)
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* 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)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F8.1-text-generation-with-lstm.ipynb)
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* [8.2: Deep dream](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/8.2-deep-dream.ipynb)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F8.2-deep-dream.ipynb)
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* [8.3: Neural style transfer](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/8.3-neural-style-transfer.ipynb)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F8.3-neural-style-transfer.ipynb)
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* [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
-)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F8.4-generating-images-with-vaes.ipynb)
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+ * [8.5: Introduction to GANs](http://nbviewer.jupyter.org/github/fchollet/deep-learning-with-python-notebooks/blob/master/8.5-introduction-to-gans.ipynb)
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](https://beta.deepnote.org/launch?template=data-science&url=https%3A%2F%2Fgithub.com%2Ffchollet%2Fdeep-learning-with-python-notebooks%2Fblob%2Fmaster%2F8.5-introduction-to-gans.ipynb)