ML-Notebooks is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
These projects were analysed and named ML-Notebooks among their alternatives. The relationship is not symmetric — how ML-Notebooks rates them is a separate judgement, made when ML-Notebooks is analysed in its own right.
calls ML-Notebooks “When you want a hand-curated set of ML notebooks, though unmaintained.”
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.