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Machine Learning Curricula · Awesome GitHub Repositories

6 repos

Awesome GitHub RepositoriesMachine Learning Curricula

Structured educational paths covering fundamental and advanced concepts in machine learning, neural networks, and data science.

Explore 6 awesome GitHub repositories matching education & learning resources · Machine Learning Curricula. Refine with filters or upvote what's useful.

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Awesome Machine Learning Curricula GitHub Repositories

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  • practical-tutorials/project-based-learning

    practical-tutorials/project-based-learning

    258,742GitHubView on GitHub↗

    This project is a centralized, community-driven repository of hands-on tutorials designed to facilitate skill acquisition through the practical construction of real-world software applications. It serves as a comprehensive directory that aggregates external documentation and instructional materials, providing a structu

    Analyze complex datasets by applying statistical methods and visualization techniques within structured data science projects.

    beginner-projectcppgolang
  • microsoft/Web-Dev-For-Beginners

    microsoft/Web-Dev-For-Beginners

    95,318GitHubView on GitHub↗

    This project is an open-source educational curriculum designed to facilitate technical skill acquisition through a structured, project-based learning framework. It serves as a centralized knowledge base that guides learners through foundational web development concepts, modern programming logic, and advanced technical

    Offers foundational training paths to develop competencies in data manipulation, statistical analysis, and machine learning.

    JavaScriptcsscurriculumeducation
  • rasbt/LLMs-from-scratch

    rasbt/LLMs-from-scratch

    85,529GitHubView on GitHub↗

    This repository serves as an educational framework for building large language models from the ground up. It provides a structured curriculum that guides learners through the end-to-end lifecycle of model development, including data processing, architecture design, and optimization. By focusing on low-level implementat

    Offers a comprehensive educational path covering the architecture, training, and implementation of large language models.

    Jupyter Notebookaiartificial-intelligencechatbot
  • microsoft/ML-For-Beginners

    microsoft/ML-For-Beginners

    83,800GitHubView on GitHub↗

    This project is an open-source educational curriculum designed to provide a structured path for developers to master machine learning and generative AI. It functions as a technical skill development platform, offering comprehensive study materials that guide learners through fundamental concepts, algorithms, and the pr

    Builds core competencies in statistical analysis, data visualization, and trend identification using industry-standard tools.

    Jupyter Notebookdata-scienceeducationmachine-learning
  • d2l-ai/d2l-zh

    d2l-ai/d2l-zh

    75,708GitHubView on GitHub↗

    This project is an open-source, interactive educational platform designed to teach deep learning through a comprehensive, code-first curriculum. It provides a structured learning path that covers foundational mathematics, modern neural network architectures, and practical optimization techniques, enabling practitioners

    Maps out a structured path from fundamental concepts to advanced neural network architectures using practical, code-first lessons.

    Pythonbookchinesecomputer-vision
  • mlabonne/llm-course

    mlabonne/llm-course

    75,340GitHubView on GitHub↗

    This project is a comprehensive educational curriculum and engineering handbook focused on the lifecycle of large language models. It serves as a structured knowledge base for machine learning practitioners, covering the fundamental mathematical and architectural principles of transformer-based sequence modeling, as we

    Explains the core mathematical principles, such as linear algebra, that underpin the functionality of modern machine learning algorithms.

    courselarge-language-modelsllm

Explore sub-tags

  • Data Science CurriculaFoundational training paths for developing competencies in statistical analysis, data manipulation, and machine learning.
  • Deep Learning CurriculaInteractive, hands-on curricula covering the fundamental and advanced concepts of neural networks.
  • Machine Learning MathematicsEducational content covering the fundamental mathematical concepts required to master machine learning.