Tutorial Notebooks

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This repository is a series of in-depth tutorials for various machine learning architectures and concepts.

All materials were created by me, unless otherwise specifically stated.

Organization

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The "Architectures" folder contains Jupyter notebooks that go over specific architectures, as well as key concepts that underlay them. Including:

• The U-Net
• The Basic Transformer

The "Concepts" folder contains Jupyter notebooks that cover specific concepts that relate to ML. More of these tutorials focus on concepts that underlay ideas like intepretability, visualization, and understanding more nuanced and specific aspects of modern ML techniques.