deeplearningzerotoall / Pytorch
Deep Learning Zero to All - Pytorch
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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/
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
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