hongseong0314 / PyTorch

Deep Learning Zero to All - Pytorch

모두를 위한 딥러닝 시즌2 : 모두가 만드는 모두를 위한 딥러닝

모두가 만드는 모두를 위한 딥러닝 시즌 2에 오신 여러분들 환영합니다.

Getting Started

아래 링크에서 슬라이드와 영상을 통해 학습을 시작할 수 있습니다.

• Slide: http://bit.ly/2VrZcWM
• YouTube: http://bit.ly/2UVk3kn

Docker 사용자를 위한 안내

동일한 실습 환경을 위해 docker 를 사용하실 분은 docker_user_guide.md 파일을 참고하세요! :)

Install Requirements

pip install -r requirements.txt

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

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PyTorch

Deep Learning Zero to All - PyTorch

모든 코드는 PyTorch 1.0.0 기준으로 작성하였습니다.

Contributions/Comments

언제나 여러분들의 참여를 환영합니다. Comments나 Pull requests를 남겨주세요

We always welcome your comments and pull requests

목차

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