# Deep Learning and Natural Language Processing with PyTorch

## Introduction to Deep Learning
- [ ] What is Deep Learning(DL)
- [ ] Evolution of Machine Learning
- [ ] Applications of Deep Learning
- [ ] The Most Use of Mathematical Knowledge & Machine Learning Algorithm
- [ ] Introduction to PyTorch
- [ ] Frameworks that ML & DL common used
- [ ] Other Module

## Pytorch Environment Set-up
- [ ] Install Anaconda
- [ ] Setting Anaconda
- [ ] Using Conda command install PyTorch
- [ ] Using pip command install PyTorch
- [ ] Setting CUDA

## Knowledge of PyTorch
- [ ] Introduction to Tensor
- [ ] Implement with Tensor
- [ ] Introduction to Mathematical operations
- [ ] Implement with Mathematical operations
- [ ] ···

## Getting Started with Simple Cases
- [ ] Linear regression
- [ ] Logistic regression

## Feedforward Neural Network
- [ ] Introduction to Feedforward Neural Network
- [ ] Implement with Feedforward Neural Network
- [ ] Introduction to Dataset
- [ ] Introduction to Convolution Layer
- [ ] Introduction to Funtional
- [ ] Introduction to Optimization Algorithm
- [ ] Introduction to Autograd
- [ ] Save & load Model
- [ ] Introduction to GPU

## Visual Tools in PyTorch
- [ ] Introduction to Visdom
- [ ] Concepts of Visdom
- [ ] Install Visdom
- [ ] Visual Interface
- [ ] Python Function tech
- [ ] vis.text
- [ ] .image
- [ ] .scatter
- [ ] .line
- [ ] .stem
- [ ] .heatmap
- [ ] .bar
- [ ] .histogram
- [ ] .boxplot
- [ ] .surf
- [ ] .contour
- [ ] .mesh
- [ ] .svg

## Convolutional Neural Network
- [ ] Introduction to Convolutional Neural Network
- [ ] Introduction to Convolution Layer
- [ ] Introduction to Pooling Layer
- [ ] Classic CNN
- [ ] LeNet-5
- [ ] ImageNet-2010
- [ ] VGGNet
- [ ] GooLeNet
- [ ] ResNet
- [ ] Example of CNN
- [ ] Example of DRN（Deep Residual Network）

## Recurrent Neural Networks
- [ ] Introduction to Recurrent Neural Networks
- [ ] Types of RNN
- [ ] Introduction to LSTM
- [ ] Variant of LSTM
- [ ] Implement of RNN

## Auto-Encoder
- [ ] Introduction to Auto-Encoder
- [ ] Implement of Auto-Encoder

## Generative Adversarial Network
- [ ] Introduction to Generative Adversarial Network
- [ ] Introduction to Deep Convolutional Generative Adversarial Network
- [ ] Example of Generative Adversarial Network

## Seq2seq Natural Language Processing
- [ ] Introduction to Seq2seq Natural Language Processing
- [ ] Example of Seq2seq Natural Language Processing

## Using PyTorch with Quantitative Finance
- [ ] Stock Prediction using Linear Regression
- [ ] Stock Prediction using Feedforward Neural Network
- [ ] Stock Prediction using Recurrent Neural Networks