霸榜GitHub！TensorFlow+PyTorch深度学习大宝库

Posted 开源最前线

tags:

篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了霸榜GitHub！TensorFlow+PyTorch深度学习大宝库相关的知识，希望对你有一定的参考价值。

开源最前线（ID：OpenSourceTop） 猿妹整编

整编自：https://github.com/rasbt/deeplearning-models


昨日，猿妹例行打开GitHub Trending，排行第一的项目成功引起了我的注意——deeplearning-models



该项目是Jupyter Notebook中TensorFlow和PyTorch的各种深度学习架构，模型和技巧的集合。


这份集合的内容到底有多丰富呢？一起来看看



传统机器学习


感知器


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/basic-ml/perceptron.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/basic-ml/perceptron.ipynb



逻辑回归


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/basic-ml/logistic-regression.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/basic-ml/logistic-regression.ipynb


Softmax Regression (Multinomial Logistic Regression)


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/basic-ml/softmax-regression.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/basic-ml/softmax-regression.ipynb



多层感知器


多层感知器


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/mlp/mlp-basic.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/mlp/mlp-basic.ipynb



具有Dropout多层感知器


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/mlp/mlp-dropout.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/mlp/mlp-dropout.ipynb



具有批量归一化的多层感知器


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/mlp/mlp-batchnorm.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/mlp/mlp-batchnorm.ipynb



具有反向传播的多层感知器


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/mlp/mlp-lowlevel.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/mlp/mlp-fromscratch__sigmoid-mse.ipynb



CNN


基础


CNN

TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/cnn/convnet.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-basic.ipynb



具有He初始化的CNN


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-he-init.ipynb



概念


用等效卷积层代替完全连接


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/fc-to-conv.ipynb


全卷积：全卷积神经网络


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-allconv.ipynb


AlexNet：AlexNet on CIFAR-10


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-alexnet-cifar10.ipynb



VGG：CNN VGG-16


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/cnn/cnn-vgg16.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-vgg16.ipynb



VGG-16 Gender Classifier Trained on CelebA


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-vgg16-celeba.ipynb



CNN VGG-19


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-vgg19.ipynb


ResNet：ResNet and Residual Blocks


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/resnet-ex-1.ipynb



ResNet-18 Digit Classifier Trained on MNIST


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-resnet18-mnist.ipynb



ResNet-18 Gender Classifier Trained on CelebA


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-resnet18-celeba-dataparallel.ipynb



ResNet-34 Digit Classifier Trained on MNIST


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-resnet34-mnist.ipynb



ResNet-34 Gender Classifier Trained on CelebA


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-resnet34-celeba-dataparallel.ipynb



ResNet-50 Digit Classifier Trained on MNIST


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-resnet50-mnist.ipynb



ResNet-50 Gender Classifier Trained on CelebA


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-resnet50-celeba-dataparallel.ipynb



ResNet-101 Gender Classifier Trained on CelebA


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-resnet101-celeba.ipynb



ResNet-152 Gender Classifier Trained on CelebA


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-resnet152-celeba.ipynb



Network in Network


Network in Network CIFAR-10 Classifier


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/nin-cifar10.ipynb 



度量学习：具有多层感知器的孪生网络


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/metric/siamese-1.ipynb



自动编码机


全连接自动编码机：自动编码机


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/autoencoder/autoencoder.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-basic.ipynb



具有解卷积/转置卷积的卷积自动编码机


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/autoencoder/ae-deconv.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-deconv.ipynb



具有解卷积的卷积自动编码机（无池化操作）


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/aer-deconv-nopool.ipynb



具有最近邻插值的卷积自动编码机


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/autoencoder/autoencoder-conv-nneighbor.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-conv-nneighbor.ipynb



具有最近邻插值的卷积自动编码机 - 在CelebA上进行训练


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-conv-nneighbor-celeba.ipynb


具有最近邻插值的卷积自动编码机 - 在Quickdraw上训练


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-conv-nneighbor-quickdraw-1.ipynb



变分自动编码机


变分自动编码机


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-var.ipynb


卷积变分自动编码机


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-conv-var.ipynb



条件变分自动编码机


条件变分自动编码机（重建丢失中带标签）


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-cvae.ipynb


条件变分自动编码机（重建损失中没有标签）


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-cvae_no-out-concat.ipynb


卷积条件变分自动编码机（重建丢失中带标签）


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-cnn-cvae.ipynb


卷积条件变分自动编码机（重建损失中没有标签）


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/autoencoder/ae-cnn-cvae_no-out-concat.ipynb



GAN


MNIST上完全连接的GAN


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/gan/gan.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/gan/gan.ipynb



MNIST上的卷积GAN


TensorFlow 1：

https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/gan/gan-conv.ipynb


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/gan/gan-conv.ipynb



具有标签平滑的MNIST上的卷积GAN


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/gan/gan-conv-smoothing.ipynb



RNN


Many-to-one: Sentiment Analysis / Classification


A simple single-layer RNN (IMDB)


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/rnn/rnn_simple_imdb.ipynb



A simple single-layer RNN with packed sequences to ignore padding characters (IMDB)


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/rnn/rnn_simple_packed_imdb.ipynb



RNN with LSTM cells (IMDB)


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/rnn/rnn_lstm_packed_imdb.ipynb



RNN with LSTM cells and Own Dataset in CSV Format (IMDB)


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/rnn/rnn_lstm_packed_own_csv_imdb.ipynb



RNN with GRU cells (IMDB)


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/rnn/rnn_gru_packed_imdb.ipynb



Multilayer bi-directional RNN (IMDB)


PyTorch：

https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/rnn/rnn_gru_packed_imdb.ipynb



●编号664，输入编号直达本文

●输入m获取文章目录

以上是关于霸榜GitHub！TensorFlow+PyTorch深度学习大宝库的主要内容，如果未能解决你的问题，请参考以下文章

稳的一比，鸿蒙霸榜Github！

连续霸榜Github！又有一个Linux神器出现了

接连两天，持续霸榜 GitHub，这款 WiFi 开源神器我爱了！

鸿蒙霸榜Github！这个叫HarmonyOS项目有什么

2020 GitHub年度报告：Java霸榜，C/C#/C++被后起之秀干翻了

霸榜GitHub热门第一多日后，Colossal-AI正式版发布