Introduction to Machine Learning with Python
Code and Jupyter notebooks for the book 'Introduction to Machine Learning with Python' by Andreas Mueller and Sarah Guido.
What is Introduction to Machine Learning with Python?
Introduction to Machine Learning with Python is a repository containing the Jupyter notebooks and code examples from the O'Reilly book of the same name. It provides a practical, executable companion to the book, allowing learners to run and experiment with machine learning concepts using Python and scikit-learn. The project includes the `mglearn` helper library for generating visualizations and managing datasets used in the book.
Beginners and students learning machine learning with Python, particularly those following the O'Reilly book. It's also useful for educators and practitioners seeking reproducible code examples for scikit-learn-based workflows.
It offers a fully reproducible, hands-on learning experience directly tied to a popular educational book, with all necessary code and datasets included. The custom `mglearn` library simplifies visualization and data handling, reducing setup friction for learners.
Overview
Notebooks and code for the book "Introduction to Machine Learning with Python"
Use Cases
Best For
- Learning machine learning fundamentals with scikit-learn
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
