GT CSE6250 Big Data Analytics for Healthcare - Deep Learning Lab Sessions
Maintained by Sungtae An stan84@gatech.edu
In this series of tutorials, we will learn how to implement a varity of Neural Networks by using PyTorch with the example problems of healthcare domain.
The contents are as follows:
- Intro to PyTorch
- Pytorch Tensor
- Converting between Tensor and ndarray (Numpy)
- Indexing and Math operations
- GPU Acceleration
- Automatic differentiation with Variable
- Feed-forward Neural Networks
- Basic usage of TensorDataset and DataLoader in Pytorch
- How to define a python class to construct neural network
- Loss function and Optimizer
- Basic trining iteration
- Convolutional Neural Networks
- How to construct a class of ConvNet with convolutional layers, pooling layers, and fully-connected layers.
- How to use PyTorch on GPU
- Difference between
trainmode andevalmode
- Recurrent Neural Networks
- Preparing data in a proper shape for RNN
- How to use Recurrent Layer modules in PyTorch
- Advanced Topics
- Coming Soon