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Title: GitHub - lizhengjava/simplified-deeplearning: Simplified implementations of deep learning related works

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卷积网络https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C/README.md
简单卷积网络示例https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C/%E7%AE%80%E5%8D%95%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C.md
经典CNN模型(LeNet and AlexNet)https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C/%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C%E8%BF%9B%E9%98%B6.ipynb
GoogLeNethttps://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C/GoogLeNet.ipynb
ResNethttps://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C/ResNet.ipynb
循环递归网络https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%BE%AA%E7%8E%AF%E9%80%92%E5%BD%92%E7%BD%91%E7%BB%9C/README.md
RNN示例https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%BE%AA%E7%8E%AF%E9%80%92%E5%BD%92%E7%BD%91%E7%BB%9C/RNN.md
LSTMhttps://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%BE%AA%E7%8E%AF%E9%80%92%E5%BD%92%E7%BD%91%E7%BB%9C/LSTM.md
基于CharRNN的古诗生成https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%BE%AA%E7%8E%AF%E9%80%92%E5%BD%92%E7%BD%91%E7%BB%9C/poetry-charRNN.ipynb
实践调参https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%AE%9E%E8%B7%B5%E8%B0%83%E5%8F%82/README.md
线性因子模型https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E7%BA%BF%E6%80%A7%E5%9B%A0%E5%AD%90%E6%A8%A1%E5%9E%8B/README.md
自编码器https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E8%87%AA%E7%BC%96%E7%A0%81%E5%99%A8/README.md
表示学习https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E8%A1%A8%E7%A4%BA%E5%AD%A6%E4%B9%A0/README.md
结构化概率模型https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E7%BB%93%E6%9E%84%E5%8C%96%E6%A6%82%E7%8E%87%E6%A8%A1%E5%9E%8B/README.md
蒙特卡洛方法https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E8%92%99%E7%89%B9%E5%8D%A1%E6%B4%9B%E6%96%B9%E6%B3%95/README.md
玻尔兹曼机https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E7%8E%BB%E5%B0%94%E5%85%B9%E6%9B%BC%E6%9C%BA/README.md
有向生成网络https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E6%9C%89%E5%90%91%E7%94%9F%E6%88%90%E7%BD%91%E7%BB%9C
生成对抗网络https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E7%94%9F%E6%88%90%E5%AF%B9%E6%8A%97%E7%BD%91%E7%BB%9C/README.md
如何贡献代码https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/pending/README.md
https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning#致谢
第一章 前言https://exacity.github.io/deeplearningbook-chinese/Chapter1_introduction/
前言介绍https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/README.md
第二章 线性代数https://exacity.github.io/deeplearningbook-chinese/Chapter2_linear_algebra/
线性代数https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E6%95%B0%E5%AD%A6%E5%9F%BA%E7%A1%80/%E7%BA%BF%E6%80%A7%E4%BB%A3%E6%95%B0.md
第三章 概率与信息论https://exacity.github.io/deeplearningbook-chinese/Chapter3_probability_and_information_theory/
概率与信息论https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E6%95%B0%E5%AD%A6%E5%9F%BA%E7%A1%80/%E6%A6%82%E7%8E%87%E4%B8%8E%E4%BF%A1%E6%81%AF%E8%AE%BA.md
第四章 数值计算https://exacity.github.io/deeplearningbook-chinese/Chapter4_numerical_computation/
数值计算https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E6%95%B0%E5%AD%A6%E5%9F%BA%E7%A1%80/%E6%95%B0%E5%80%BC%E8%AE%A1%E7%AE%97.md
第五章 机器学习基础https://exacity.github.io/deeplearningbook-chinese/Chapter5_machine_learning_basics/
机器学习基础与实践https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%9F%BA%E7%A1%80%E4%B8%8E%E5%AE%9E%E8%B7%B5/README.md
第六章 深度前馈网络https://exacity.github.io/deeplearningbook-chinese/Chapter6_deep_feedforward_networks/
深度前馈网络https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E6%B7%B1%E5%BA%A6%E5%89%8D%E9%A6%88%E7%BD%91%E7%BB%9C/README.md
第七章 深度学习中的正则化https://exacity.github.io/deeplearningbook-chinese/Chapter7_regularization/
深度学习中的正则化https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E4%B8%AD%E7%9A%84%E6%AD%A3%E5%88%99%E5%8C%96/README.md
第八章 深度模型中的优化https://exacity.github.io/deeplearningbook-chinese/Chapter8_optimization_for_training_deep_models/
深度学习中的优化https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E4%B8%AD%E7%9A%84%E4%BC%98%E5%8C%96/README.md
第九章 卷积网络https://exacity.github.io/deeplearningbook-chinese/Chapter9_convolutional_networks/
卷积网络https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C/README.md
第十章 序列建模：循环和递归网络https://exacity.github.io/deeplearningbook-chinese/Chapter10_sequence_modeling_rnn/
循环递归网络https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%BE%AA%E7%8E%AF%E9%80%92%E5%BD%92%E7%BD%91%E7%BB%9C/README.md
第十一章 实践方法论https://exacity.github.io/deeplearningbook-chinese/Chapter11_practical_methodology/
实践调参https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E5%AE%9E%E8%B7%B5%E8%B0%83%E5%8F%82/README.md
第十二章 应用https://exacity.github.io/deeplearningbook-chinese/Chapter12_applications/
第十三章 线性因子模型https://exacity.github.io/deeplearningbook-chinese/Chapter13_linear_factor_models/
线性因子模型https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E7%BA%BF%E6%80%A7%E5%9B%A0%E5%AD%90%E6%A8%A1%E5%9E%8B/README.md
第十四章 自编码器https://exacity.github.io/deeplearningbook-chinese/Chapter14_autoencoders/
自编码器https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E8%87%AA%E7%BC%96%E7%A0%81%E5%99%A8/README.md
第十五章 表示学习https://exacity.github.io/deeplearningbook-chinese/Chapter15_representation_learning/
表示学习https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E8%A1%A8%E7%A4%BA%E5%AD%A6%E4%B9%A0/README.md
第十六章 深度学习中的结构化概率模型https://exacity.github.io/deeplearningbook-chinese/Chapter16_structured_probabilistic_modelling/
结构化概率模型https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E7%BB%93%E6%9E%84%E5%8C%96%E6%A6%82%E7%8E%87%E6%A8%A1%E5%9E%8B/README.md
第十七章 蒙特卡罗方法https://exacity.github.io/deeplearningbook-chinese/Chapter17_monte_carlo_methods/
蒙特卡洛方法https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E8%92%99%E7%89%B9%E5%8D%A1%E6%B4%9B%E6%96%B9%E6%B3%95/README.md
第十八章 面对配分函数https://exacity.github.io/deeplearningbook-chinese/Chapter18_confronting_the_partition_function/
第十九章 近似推断https://exacity.github.io/deeplearningbook-chinese/Chapter19_approximate_inference/
第二十章 深度生成模型https://exacity.github.io/deeplearningbook-chinese/Chapter20_deep_generative_models/
玻尔兹曼机https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E7%8E%BB%E5%B0%94%E5%85%B9%E6%9B%BC%E6%9C%BA/README.md
有向生成网络https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E6%9C%89%E5%90%91%E7%94%9F%E6%88%90%E7%BD%91%E7%BB%9C
生成对抗网络https://patch-diff.githubusercontent.com/lizhengjava/simplified-deeplearning/blob/master/%E7%94%9F%E6%88%90%E5%AF%B9%E6%8A%97%E7%BD%91%E7%BB%9C
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