/Pytorch-Tutorials

Pytorch-Tutorials

So you're looking to learn some PyTorch? Here's a set of useful pytorch tutorials for you.

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Introduction:

  1. What is a Tensor (BBBBoring): https://pytorch.org/tutorials/beginner/basics/tensorqs_tutorial.html
  2. Building Models with PyTorch: https://pytorch.org/tutorials/beginner/introyt/modelsyt_tutorial.html
  3. Loading Datasets: https://pytorch.org/tutorials/beginner/basics/data_tutorial.html
  4. Gradients (Maybe skip): https://pytorch.org/tutorials/beginner/basics/autogradqs_tutorial.html
  5. Training: https://pytorch.org/tutorials/beginner/basics/optimization_tutorial.html
  6. Saving and Loading Models: https://pytorch.org/tutorials/beginner/basics/saveloadrun_tutorial.html

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Time Series Learning

  1. 1 Intorduction to LSTMS: https://towardsdatascience.com/pytorch-lstms-for-time-series-data-cd16190929d7
  2. 2 LSTMS (Practical intro): https://colab.research.google.com/github/dlmacedo/starter-academic/blob/master/content/courses/deeplearning/notebooks/pytorch/Time_Series_Prediction_with_LSTM_Using_PyTorch.ipynb

Robot Pushing:

  1. BAIR robot pushing dataset: https://sites.google.com/berkeley.edu/robotic-interaction-datasets
  2. Code to load: https://github.com/edenton/svg/blob/master/data/convert_bair.py
  3. SVG video predictor: https://github.com/WillMandil001/SPOTS/blob/main/models/universal_models/universal_networks/SVG.py (https://proceedings.mlr.press/v80/denton18a.html, https://proceedings.neurips.cc/paper/2019/hash/f7177163c833dff4b38fc8d2872f1ec6-Abstract.html)

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