vsmolyakov/ml_algo_in_depth
ML algorithms in depth
This resource provides practical examples and code for understanding how various machine learning algorithms work. It takes you through the inner workings of models like decision trees, neural networks, and clustering methods, showing you how they process data and produce results. It's designed for data scientists, analysts, or engineers who want to deepen their knowledge of ML fundamentals beyond just using libraries.
274 stars. No commits in the last 6 months.
Use this if you are a data professional seeking to understand the mathematical intuition and implementation details behind common machine learning algorithms and their applications.
Not ideal if you are looking for a plug-and-play library to immediately apply machine learning models to your data without diving into the underlying theory.
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Python
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Last pushed
Sep 27, 2024
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