/CSE6250BDH-LAB-DL

GT CSE6250 Big Data Analytics for Healthcare - Deep Learning Lab Sessions

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CSE6250BDH-LAB-DL

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:

  1. Intro to PyTorch
    • Pytorch Tensor
    • Converting between Tensor and ndarray (Numpy)
    • Indexing and Math operations
    • GPU Acceleration
    • Automatic differentiation with Variable
  2. 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
  3. 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 train mode and eval mode
  4. Recurrent Neural Networks
    • Preparing data in a proper shape for RNN
    • How to use Recurrent Layer modules in PyTorch
  5. Advanced Topics
    • Coming Soon