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.

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

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 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

Name		Name	Last commit message	Last commit date
Latest commit History 78 Commits
imgs		imgs
.gitignore		.gitignore
01.0 - Tensor Manipulation.ipynb		01.0 - Tensor Manipulation.ipynb
02.0 - Linear Regression.ipynb		02.0 - Linear Regression.ipynb
03.0 - Minimizing Cost, Gradient Descent.ipynb		03.0 - Minimizing Cost, Gradient Descent.ipynb
04.0 - Multivariable Linear Regression.ipynb		04.0 - Multivariable Linear Regression.ipynb
04.1 - Loading Data.ipynb		04.1 - Loading Data.ipynb
05.0 - Logisitic Regression.ipynb		05.0 - Logisitic Regression.ipynb
06.0 - Softmax Classification.ipynb		06.0 - Softmax Classification.ipynb
06.1 - Fancy Softmax Classification.ipynb		06.1 - Fancy Softmax Classification.ipynb
07.0 - Tips.ipynb		07.0 - Tips.ipynb
07.1 - Introduction to MNIST.ipynb		07.1 - Introduction to MNIST.ipynb
08.0 - About the Neural Network.md		08.0 - About the Neural Network.md
08.1 - About XOR.ipynb		08.1 - About XOR.ipynb
08.2 - XOR with Neural Net.ipynb		08.2 - XOR with Neural Net.ipynb
08.3 - XOR with Wide and Deep Neural Network.ipynb		08.3 - XOR with Wide and Deep Neural Network.ipynb
08.4 - Backpropagation with MNIST.ipynb		08.4 - Backpropagation with MNIST.ipynb
09.0 - About Optimizers.md		09.0 - About Optimizers.md
09.1 - About Adam with MNIST Classifier.ipynb		09.1 - About Adam with MNIST Classifier.ipynb
09.2 - About Activiations.md		09.2 - About Activiations.md
09.3 - About Relu Activation with MNIST Classifier.ipynb		09.3 - About Relu Activation with MNIST Classifier.ipynb
09.3 - About Weights Initlizaition.md		09.3 - About Weights Initlizaition.md
09.4 - About Xavier Init with MNIST Classifier.ipynb		09.4 - About Xavier Init with MNIST Classifier.ipynb
09.5 - Relu + Xavier MNIST Classifier.ipynb		09.5 - Relu + Xavier MNIST Classifier.ipynb
09.6 - About Dropout.md		09.6 - About Dropout.md
09.7 - About Dropout with MNIST Classifier.ipynb		09.7 - About Dropout with MNIST Classifier.ipynb
09.8 - About Batch Normalization.md		09.8 - About Batch Normalization.md
09.9 - BatchNorm + Dropout + Xavier with MNIST Classifier.ipynb		09.9 - BatchNorm + Dropout + Xavier with MNIST Classifier.ipynb
10.0 - About CNN.md		10.0 - About CNN.md
10.1 - CNN with MNIST Classifier.ipynb		10.1 - CNN with MNIST Classifier.ipynb
10.2 - Deep CNN with MNIST Classifier.ipynb		10.2 - Deep CNN with MNIST Classifier.ipynb
10.3.1 - Visdom Example.ipynb		10.3.1 - Visdom Example.ipynb
10.3.2 - MNIST-CNN with Visdom.ipynb		10.3.2 - MNIST-CNN with Visdom.ipynb
10.4.1 - ImageFolder1.ipynb		10.4.1 - ImageFolder1.ipynb
10.4.2 - ImageFolder2.ipynb		10.4.2 - ImageFolder2.ipynb
10.5.0 - About the VGG net.md		10.5.0 - About the VGG net.md
10.5.1 - Advanced CNN(Vgg).ipynb		10.5.1 - Advanced CNN(Vgg).ipynb
10.5.2 - VGG for cifar10.ipynb		10.5.2 - VGG for cifar10.ipynb
10.6.0 - About ResNet.md		10.6.0 - About ResNet.md
10.6.1 - Advanced CNN (ResNet).ipynb		10.6.1 - Advanced CNN (ResNet).ipynb
10.6.2 - Advanced CNN (ResNet_Cifar10).ipynb		10.6.2 - Advanced CNN (ResNet_Cifar10).ipynb
README.md		README.md
data-01-test-score.csv		data-01-test-score.csv
data-02-stock_daily.csv		data-02-stock_daily.csv
data-03-diabetes.csv		data-03-diabetes.csv
data-04-zoo.csv		data-04-zoo.csv

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Deep Learning Zero to All 2: PyTorch

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

Getting Started

Instruction for Docker User.

Install Requirements

PyTorch

Contributions/Comments

Index

PART 1: Machine Learning & PyTorch Basic

PART 2: Neural Network

PART 3: Convolutional Neural Network

PART 4: Recurrent Neural Network

About

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steveive8/Deep-Learning-Zero-To-All-2-PyTorch

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Repository files navigation

Deep Learning Zero to All 2: PyTorch

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

Getting Started

Instruction for Docker User.

Install Requirements

PyTorch

Contributions/Comments

Index

PART 1: Machine Learning & PyTorch Basic

PART 2: Neural Network

PART 3: Convolutional Neural Network

PART 4: Recurrent Neural Network

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