/tutorials

This is a set of tutorials with code examples for future Yochai and friends

Primary LanguageJupyter Notebook

tutorials

This is a set of tutorials with code examples for future Yochai and friends

Turorials finished

  1. scipy/Basic Fourier analysis - DFT.ipynb-basic theory and use cases of regular fourier analisys with scipy library https://app.reviewnb.com/vyohai/tutorials/blob/main/scipy%2FBasic%20Fourier%20analysis%20-%20DFT.ipynb

  2. scipy/The short-time fourier transform.ipynb-basic theory and use cases of time-based fourier analisys with scipy library https://app.reviewnb.com/vyohai/tutorials/blob/main/scipy/The%20short%20time%20fourier%20transform.ipynb/

  3. scipy/Quaternions.ipynb-basic theory and use cases Quaternion orientation representation with scipy library https://app.reviewnb.com/vyohai/tutorials/blob/main/scipy%2FQuaternions.ipynb

  4. scipy/Basic filter Design.ipynb- basic theory and use cases of IIR and FIR linear filters with scipy library https://app.reviewnb.com/vyohai/tutorials/blob/main/scipy%2FBasic%20filter%20Design.ipynb

Tutorials TBD

  1. scipy/scipy profiling.ipynb-TBD
  2. pytorch/tensors.ipynb-basic theory and use cases of tensors with pytorch library * based on: https://pytorch.org/docs/stable/tensors.html
  3. pytorch/torch.utils.data.ipynb-basic theory and use cases of utils.data(dataloaders) with pytorch library * based on: https://pytorch.org/docs/stable/data.html
  4. pytorch/torch.nn.Module.ipynb-basic theory and use cases of nn.Module(neural network model object) with pytorch library * based on: https://pytorch.org/docs/stable/generated/torch.nn.Module.html
  5. pytorch/autograd.ipynb-basic theory and use cases of autograd(pytorch diffrentation engine) with pytorch library * based on: https://docs.google.com/document/d/1MymdFxJxFbqUiWdoJpNblokygiiOfMfP16Z6paoKRIU/edit#heading=h.7klfnw5rld6n
  6. pytorch/torch.optim.ipynb-basic theory and use cases of torch.optim(diffrent gradient decsent optimization algorithms) with pytorch library * based on: https://pytorch.org/docs/stable/optim.html
  7. pytorch/nn.Linear.ipynb-basic theory and use cases of nn.Linear(linear neural networks) with pytorch library * based on: https://pytorch.org/docs/stable/generated/torch.nn.Linear.html
  8. pytorch/LSTM.ipynb-basic theory and use cases of LSTM with pytorch library * based on: https://pytorch.org/docs/stable/generated/torch.nn.LSTM.html * and: https://pytorch.org/docs/stable/generated/torch.nn.LSTMCell.html#torch.nn.LSTMCell
  9. pytorch/profiler.ipynb-basic theory and use cases of profiler with pytorch library * based on: https://pytorch.org/tutorials/recipes/recipes/profiler_recipe.html * and: https://levelup.gitconnected.com/pytorch-official-blog-detailed-pytorch-profiler-v1-9-7a5ca991a97b * and with wandb(and GPU): https://wandb.ai/wandb/trace/reports/Using-the-PyTorch-Profiler-with-W-B--Vmlldzo5MDE3NjU
  10. wandb/Track experiements.ipynb-basic use cases of wandb experiements tracking capabilities * based on:https://docs.wandb.ai/guides/track
  11. pack training applications/pack_example.ipynb-tutorial on how to create a python training application for Google cloud