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Deep Learning Zero to All 2: PyTorch

Edited By Steve Ive with English sub and additional Contents. + Fixing bugs

Study Scripts for Deep Learning Zero To All, Part 2, Pytorch

Getting Started

You can start learning below links with scripts and youtube channel.

Instruction for Docker User.

Please check below file who want to use Docker for same practice environment. :) docker_user_guide.md

Install Requirements

pip install -r requirements.txt

Install PyTorch from website: https://pytorch.org/

PyTorch

Deep Learning Zero to All - PyTorch

These codes written base on PyTorch 1.0.0.

Contributions/Comments

Always welcome your participation. Please write comments or leave pull requests.

We always welcome your comments and pull requests

Index

PART 1: Machine Learning & PyTorch Basic

  • Lab-01-1 Tensor Manipulation 1
  • Lab-01-2 Tensor Manipulation 2
  • Lab-02 Linear regression
  • Lab-03 Deeper Look at GD
  • Lab-04-1 Multivariable Linear regression
  • Lab-04-2 Loading Data
  • Lab-05 Logistic Regression
  • Lab-06 Softmax Classification
  • Lab-07-1 Tips
  • Lab-07-2 MNIST Introduction

PART 2: Neural Network

  • Lab-08-1 Perceptron
  • Lab-08-2 Multi Layer Perceptron
  • Lab-09-1 ReLU
  • Lab-09-2 Weight initialization
  • Lab-09-3 Dropout
  • Lab-09-4 Batch Normalization

PART 3: Convolutional Neural Network

  • Lab-10-0 Convolution Neural Networkintro
  • Lab-10-1 Convolution
  • Lab-10-2 mnist cnn
  • Lab-10-3 visdom
  • Lab-10-4-1 ImageFolder1
  • Lab-10-4-2 ImageFolder2
  • Lab-10-5 Advance CNN(VGG)
  • Lab-10-6-1 Advanced CNN(RESNET-1)
  • Lab-10-6-2 Advanced CNN(RESNET-2)
  • Lab-10-7 Next step of CNN

PART 4: Recurrent Neural Network

  • Lab-11-0 RNN intro
  • Lab-11-1 RNN basics
  • Lab-11-2 RNN hihello and charseq
  • Lab-11-3 Long sequence
  • Lab-11-4 RNN timeseries
  • Lab-11-5 RNN seq2seq
  • Lab-11-6 PackedSequence