PyTorch intro

Read over (or run if you need practice) notebooks 1-Basics. Run all of notebook 2-NN basics and workflows. Rerun notebook 2 and make the task a bit more difficult by:

• adding Gaussian standard noise to the data. (w/ at least sigma=0.01)

• adjust training hyperparameters as necessary to achieve good results.

For extra credit run notebook 3. If you do not have access to a GPU, use free tier Google collab GPU with instructions outlined in https://flexie.github.io/CSE-8803-Twin/schedule.html.

The notebooks can be downloaded from here

• Basics - pytorch_101.ipynb

• NN Basics & Workflows - pytorch_102.ipynb

• GPUs - Torch_test_GPU_CPU.ipynb