This library gives a modular design for better control of gradient passing between architecture components. Useful for architectures not using a traditional forward and backward pass.
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Updated
May 7, 2024 - Jupyter Notebook
This library gives a modular design for better control of gradient passing between architecture components. Useful for architectures not using a traditional forward and backward pass.
Different machine learning approaches on classifying customers who are most likely to purchase an offer. Made with Jupyter Notebook, scikit-learn, and other helpful python packages.
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