Python-为深度学习Python一书的Jupyter笔记本代码示例

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为“深度学习Python”一书的Jupyter笔记本代码示例
Python-为深度学习Python一书的Jupyter笔记本代码示例.zip
  • deep-learning-with-r-notebooks-master
  • notebooks
  • dream
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内容介绍
# 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)](https://www.manning.com/books/deep-learning-with-r). 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)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/2.1-a-first-look-at-a-neural-network.nb.html) | [R Markdown (Rmd)](notebooks/2.1-a-first-look-at-a-neural-network.Rmd) | | 3.4: Classifying movie reviews: a binary classification example | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/3.4-classifying-movie-reviews.nb.html) | [R Markdown (Rmd)](notebooks/3.4-classifying-movie-reviews.Rmd) | | 3.5: Classifying newswires: a multi-class classification example | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/3.5-classifying-newswires.nb.html) | [R Markdown (Rmd)](notebooks/3.5-classifying-newswires.Rmd) | | 3.6: Predicting house prices: a regression example | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/3.6-predicting-house-prices.nb.html) | [R Markdown (Rmd)](notebooks/3.6-predicting-house-prices.Rmd) | | 4.4: Overfitting and underfitting | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/4.4-overfitting-and-underfitting.nb.html) | [R Markdown (Rmd)](notebooks/4.4-overfitting-and-underfitting.Rmd) | | 5.1: Introduction to convnets | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/5.1-introduction-to-convnets.nb.html) | [R Markdown (Rmd)](notebooks/5.1-introduction-to-convnets.Rmd) | | 5.2: Using convnets with small datasets | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/5.2-using-convnets-with-small-datasets.nb.html) | [R Markdown (Rmd)](notebooks/5.2-using-convnets-with-small-datasets.Rmd) | | 5.3: Using a pre-trained convnet | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/5.3-using-a-pretrained-convnet.nb.html) | [R Markdown (Rmd)](notebooks/5.3-using-a-pretrained-convnet.Rmd) | | 5.4: Visualizing what convnets learn | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/5.4-visualizing-what-convnets-learn.nb.html) | [R Markdown (Rmd)](notebooks/5.4-visualizing-what-convnets-learn.Rmd) | | 6.1: One-hot encoding of words or characters | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/6.1-one-hot-encoding-of-words-or-characters.nb.html) | [R Markdown (Rmd)](notebooks/6.1-one-hot-encoding-of-words-or-characters.Rmd) | | 6.1: Using word embeddings | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/6.1-using-word-embeddings.nb.html) | [R Markdown (Rmd)](notebooks/6.1-using-word-embeddings.Rmd) | | 6.2: Understanding recurrent neural networks | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/6.2-understanding-recurrent-neural-networks.nb.html) | [R Markdown (Rmd)](notebooks/6.2-understanding-recurrent-neural-networks.Rmd) | | 6.3: Advanced usage of recurrent neural networks | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/6.3-advanced-usage-of-recurrent-neural-networks.nb.html) | [R Markdown (Rmd)](notebooks/6.3-advanced-usage-of-recurrent-neural-networks.Rmd) | | 6.4: Sequence processing with convnets | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/6.4-sequence-processing-with-convnets.nb.html) | [R Markdown (Rmd)](notebooks/6.4-sequence-processing-with-convnets.Rmd) | | 8.1: Text generation with LSTM | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/8.1-text-generation-with-lstm.nb.html) | [R Markdown (Rmd)](notebooks/8.1-text-generation-with-lstm.Rmd) | | 8.2: Deep Dream | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/8.2-deep-dream.nb.html) | [R Markdown (Rmd)](notebooks/8.2-deep-dream.Rmd) | | 8.3: Neural style transfer | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/8.3-neural-style-transfer.nb.html) | [R Markdown (Rmd)](notebooks/8.3-neural-style-transfer.Rmd) | | 8.4: Generating images | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/8.4-generating-images-with-vaes.nb.html) | [R Markdown (Rmd)](notebooks/8.4-generating-images-with-vaes.Rmd) | | 8.5: Introduction to generative adversarial networks | [Notebook (HTML)](https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/8.5-introduction-to-gans.nb.html) | [R Markdown (Rmd)](notebooks/8.5-introduction-to-gans.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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