# llsourcell/learn_machine_learning_in_3_months

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7,616 stars · 2,314 forks

## Links

- GitHub: https://github.com/llSourcell/Learn_Machine_Learning_in_3_Months
- awesome-repositories: https://awesome-repositories.com/repository/llsourcell-learn-machine-learning-in-3-months.md

## Description

This project is a machine learning curriculum and educational course repository designed as a structured three-month study plan. It provides a guided path for mastering data science and artificial intelligence using the Python programming language.

The repository organizes learning materials and code examples to cover mathematics, algorithms, and deep learning fundamentals. It uses a modular curriculum structure to break the domain into discrete monthly and weekly segments.

The project functions as a curated resource map that aligns source code and notes with external instructional videos and third-party educational content.

## Tags

### Education & Learning Resources

- [Machine Learning Curricula](https://awesome-repositories.com/f/education-learning-resources/machine-learning-curricula.md) — Implements a comprehensive three-month educational program and syllabus for learning machine learning fundamentals.
- [Weekly Module Progressions](https://awesome-repositories.com/f/education-learning-resources/curriculum-structures/weekly-module-progressions.md) — Provides a guided weekly sequence of educational modules that incrementally build machine learning skills.
- [Educational Code Repositories](https://awesome-repositories.com/f/education-learning-resources/educational-code-repositories.md) — Provides a source code collection specifically curated to accompany a series of instructional videos.
- [Curated Learning Paths](https://awesome-repositories.com/f/education-learning-resources/educational-resources/courses-training-certifications/technical-learning-roadmaps/curated-learning-paths.md) — Organises external educational content into a sequential timeline to guide learners through a specific pedagogical path.
- [AI & Machine Learning Education](https://awesome-repositories.com/f/education-learning-resources/technical-domain-education/ai-machine-learning-education.md) — Provides educational content covering neural network theory, machine learning algorithms, and practical implementation guides. ([source](https://github.com/llsourcell/learn_machine_learning_in_3_months#readme))
- [Deep Learning Fundamentals](https://awesome-repositories.com/f/education-learning-resources/deep-learning-curriculum/deep-learning-fundamentals.md) — Covers core neural network concepts and practical implementation as part of a guided learning path.
- [Machine Learning Guides](https://awesome-repositories.com/f/education-learning-resources/python-programming-guides/machine-learning-guides.md) — Provides a guided path for mastering data science and AI using the Python programming language.
- [Topic-Based Resource Organization](https://awesome-repositories.com/f/education-learning-resources/topic-based-resource-organization.md) — Structures source code and notes into folders based on specific machine learning concepts.

### Artificial Intelligence & ML

- [Machine Learning Education](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning-education.md) — Provides resources focused on teaching the mathematical and theoretical foundations of machine learning.

### Part of an Awesome List

- [Data Science Foundations](https://awesome-repositories.com/f/awesome-lists/learning/data-science-foundations.md) — Offers foundational literature and educational resources for learning data science concepts.