Hey all, I'm Sebastian Raschka, author of Machine Learning with Pytorch and Scikit-Learn. Please feel free to ask me anything!

• coral-ordinal

  2 75 0.0 Python

  Tensorflow Keras implementation of ordinal regression using consistent rank logits (CORAL) by Cao et al. (2019)

Also, I often need to do some custom stuff for my research projects. E.g., take CORAL and CORN as an example (https://raschka-research-group.github.io/coral-pytorch/). Here, I needed custom losses and slight modifications to the forward pass. This was relatively easy to do in PyTorch. Someone was so kind to port it to TensorFlow/Keras (https://github.com/ck37/coral-ordinal/tree/master/coral_ordinal), but the code is much more complicated. For research and tinkering, I much prefer working with PyTorch.

• corn-ordinal-neuralnet

  1 20 0.0 Python

  Code and experiments for "Deep Neural Networks for Rank Consistent Ordinal Regression based on Conditional Probabilities"

  

You could implement all the things PyTorch Lightning does yourself, but it would be more messy and more work. I kind of did that for logging and checkpointing, and it was very hard to maintain and read for others. Here's an example :P https://github.com/Raschka-research-group/corn-ordinal-neuralnet/tree/main/model-code/refactored-version/cnn-image/helper_files

• InfluxDB

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• Pytorch

  341 78,205 10.0 Python

  Tensors and Dynamic neural networks in Python with strong GPU acceleration

  

No. The focus is on the PyTorch API and explaining how people can use PyTorch. However, there is no walkthrough explaining all the underlying code in https://github.com/pytorch/pytorch/tree/master/torch. This is an interesting idea, but that would be for a different kind of book :P

Suggest a related project