pytorch教程(持续更新中)

What is PyTorch?

目录

 

初学者教程

    PyTorch深度学习：60分钟闪电战

        What is PyTorch?

        Autograd: automatic differentiation

        Neural Network

        Training a classifier

        Optional: Data Parallelism

    PyTroch for former Torch users

        Tensor

        Autograd

        nn package

        Multi-GPU examples

    通过实例学习pytorch

        Tensor

        Autograd

        nn package

        Examples

    Transfer Learning turorial

        Load Data

        Training the model

        Finetuning the convnet

        ConvNet as fixed feature extractor

    数据导入及处理教程

        Dataset class

        Transforms

        Iterating through the dataset

        Afterword: torchvision

    通过PyTorch深入学习NLP

        Introduction to PyTorch

        Deep Learning with PyTorch

        Word Embeddings: Encoding Lexical Semantics

        Advanced: Making Dynamic Decisions and the Bi-LSTM CRF

中级教程

    使用CharacterLevel  RNN进行名字分类

        Preparing the Data

        Creating the Network

        Training

        Evaluating the Results

        Exercises

    使用CharacterLevel  RNN进行名字生成

        Preparing the Data

        Creating the Network

        Training

        Sampling the Network

        Exercises

    Translation with a Sequence to Sequence Network and Attention

        Loading data files

        The Seq2Seq Model

        Training

        Evaluation

        Training and Evaluating

        Exercises

    强化学习（DQN）教程

        Replay Memory

        DQN algorithm

        Training

    使用PyTorch编写分布式应用程序

        SetUp

        Point-to-Point Communication

        Collective Communication

        Distribution Training

        Advanced Topics

    Spatial Transformer Network Tutorial

        Loading the Data

        Depicting spatial transformer networks

        Training the model

        Visualizing the STN results

高级教程

    PyTorchs神经传递

        Introduction

        PyTorch implementation

    使用numpy和SciPy创建扩展

        Parameter-less example

        Parametrized example

    使用ONNX将模型从PyTorch传输到Caffe和Mobile

        Transfering SRResNet using ONNX

        Running the model on mobile devices

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