ML From Scratch
Bare bones NumPy implementations of machine learning models and algorithms.
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Homemade Machine Learning
Python examples of popular ML algorithms with interactive Jupyter demos.
Day 43 since launch · Launched 25 August 2026
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What is Homemade Machine Learning?
Homemade Machine Learning is a collection of from-scratch Python implementations of popular machine learning algorithms, each with interactive Jupyter demos and the math explained step by step.
Pros
- Every algorithm implemented from scratch
- Interactive Jupyter demos
- Math explained alongside the code
Cons
- For learning, not production use
- Covers classical ML more than deep learning
Who should use Homemade Machine Learning
Learners who want to truly understand ML algorithms by building them.
Who may not need it
Practitioners who just need to apply scikit-learn.
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