GT ECE4782 Biosystems Analysis - Deep Learning Lab Series
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 biosystems and healthcare domain.
You may install PyTorch locally to run Jupyter Notebooks at your side.
We will briefly cover the following topics:
- 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