kmkolasinski/deep-learning-notes resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1347 stars · 263 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Jupyter Notebook experiments and seminar presentations on deep learning topics, including capsule pooling, custom optimizers, SELU regularization, and tf.data oversampling. It serves as educational material and research notes rather than a production library.

Use cases

• learn deep learning concepts through hands-on notebook experiments
• understand how to implement a custom gradient descent optimizer
• see how SELU self-normalizing regularization works in Keras
• learn oversampling with tf.data.Dataset for imbalanced datasets
• find deep learning seminar presentations and study materials

When to choose

• you want educational notebooks explaining deep learning techniques
• you are exploring experimental ideas like capsule pooling or max-normed optimizers
• you need examples of Keras regularizers or tf.data pipelines

When to avoid

• you need a production-ready, maintained library with a license and stable API
• you want installable packages rather than notebooks to read and run
• you need actively updated content - the repo has not seen recent releases

Facets

learning-resource · maturity maintenance

deep-learning machine-learning data-science deep-learning machine-learning tutorials python jupyter-notebooks experiments keras tensorflow seminars educational

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markdown · JSON · MCP: product_card(name="kmkolasinski/deep-learning-notes")