krasserm/machine-learning-notebooks
Stanford Machine Learning course exercises implemented with scikit-learn
This project provides practical, high-level examples for solving common machine learning problems like regression, classification, and clustering. It takes problem descriptions from the Stanford Machine Learning course and shows how to implement solutions using Python's scikit-learn library. This is ideal for developers learning Python's machine learning ecosystem.
353 stars. No commits in the last 6 months.
Use this if you are a developer familiar with machine learning concepts and want to see how to apply them using scikit-learn for common problems.
Not ideal if you are new to machine learning basics or need detailed introductions to Python's scientific programming libraries like NumPy or pandas.
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Jupyter Notebook
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Last pushed
Nov 18, 2020
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