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The Hundred-Page Machine Learning Book is the official companion repository for The Hundred-Page Machine Learning Book written by machine learning researcher Andriy Burkov. The repository contains Python code used to generate the figures, visualizations, and illustrative examples presented in the book. Its purpose is to help readers better understand the concepts explained in the text by allowing them to run and experiment with the underlying code themselves. The book itself provides a concise overview of machine learning theory and practice, covering topics such as supervised learning, unsupervised learning, neural networks, and optimization algorithms. The repository complements these explanations by offering practical implementations that demonstrate how various algorithms behave when applied to data. Readers can explore the scripts to reproduce diagrams and observe how mathematical concepts translate into working code.
Features
- Python scripts used to reproduce visualizations from the book
- Code examples demonstrating core machine learning concepts
- Implementations illustrating algorithms discussed in the text
- Educational resource for experimenting with ML techniques
- Simple and readable code designed for learning purposes
- Companion materials supporting a concise machine learning guide
Project Samples
