calls machine_learning_complete “choose if you want a comprehensive but stale notebook collection.”
100-Days-Of-ML-Code中文版
machine_learning_complete 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 machine_learning_complete among their alternatives. The relationship is not symmetric — how machine_learning_complete rates them is a separate judgement, made when machine_learning_complete is analysed in its own right.
calls machine_learning_complete “choose if you want a comprehensive but stale notebook collection.”
100-Days-Of-ML-Code中文版
calls machine_learning_complete “choose it for a broad machine learning notebook survey, though it is inactive and not deep-learning-focused.”
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
calls machine_learning_complete “When you want a broad set of ML notebooks despite being 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.
calls machine_learning_complete “Older but still useful ML-only notebook collection; choose when you need a compact ML tutorial set, not a full AI roadmap.”
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