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Edited By Steve Ive, with English Sub and Additional Content _ Fixing Bugs: Study for Deep Learning Zero To All, Part 2, Pytorch

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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

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

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Edited By Steve Ive, with English Sub and Additional Content _ Fixing Bugs: Study for Deep Learning Zero To All, Part 2, Pytorch

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