Related Issues (17)
- Implement the crossentropy loss function
- Restructure project directory into several subdirectories
- Create a class for handling console output
- Implement console output to provide training feedback
- Derive the loss subclass from a metric class and add in an accuracy metric
- Add an option to attach an activation directly to a layer
- Add helper functions for working with tensors
- Make all neural net operator objects derive from single class
- Arrange sections of library into namespaces.
- Implement iterators on the Tensor class and make use of STL algorithms.
- Clean up neural network operators
- Implement a larger variety of layers
- Convert training from full-batch to mini-batch
- Make trainer use testing and validation dataset partitions
- Add python API.
- Check condition in line
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