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Jupyter notebooks for the code samples of the book "Deep Learning with Python"

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R Markdown Notebooks for "Deep Learning with R"

This repository contains R Markdown notebooks implementing the code samples found in the book Deep Learning with R (Manning Publications). 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.


Description Notebook Source Code
2.1: A first look at a neural network Notebook (HTML) R Markdown (Rmd)
3.5: Classifying movie reviews: a binary classification example Notebook (HTML) R Markdown (Rmd)
3.6: Classifying newswires: a multi-class classification example Notebook (HTML) R Markdown (Rmd)
3.7: Predicting house prices: a regression example Notebook (HTML) R Markdown (Rmd)
4.4: Overfitting and underfitting Notebook (HTML) R Markdown (Rmd)
5.1: Introduction to convnets Notebook (HTML) R Markdown (Rmd)
5.2: Using convnets with small datasets Notebook (HTML) R Markdown (Rmd)
5.3: Using a pre-trained convnet Notebook (HTML) R Markdown (Rmd)
5.4: Visualizing what convnets learn Notebook (HTML) R Markdown (Rmd)
6.1: One-hot encoding of words or characters Notebook (HTML) R Markdown (Rmd)
6.1: Using word embeddings Notebook (HTML) R Markdown (Rmd)
6.2: Understanding recurrent neural networks Notebook (HTML) R Markdown (Rmd)
6.3: Advanced usage of recurrent neural networks Notebook (HTML) R Markdown (Rmd)
6.4: Sequence processing with convnets Notebook (HTML) R Markdown (Rmd)
8.1: Text generation with LSTM Notebook (HTML) R Markdown (Rmd)
8.2: Deep Dream Notebook (HTML) R Markdown (Rmd)
8.3: Neural style transfer Notebook (HTML) R Markdown (Rmd)
8.4: Generating images Notebook (HTML) R Markdown (Rmd)
8.5: Introduction to generative adversarial networks Notebook (HTML) R Markdown (Rmd)

LICENSE

MIT License

Copyright (c) 2017 François Chollet
Copyright (c) 2017 J.J. Allaire

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.

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