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Machine Learning Education · Awesome GitHub Repositories

6 repos

Awesome GitHub RepositoriesMachine Learning Education

Materials focused on teaching fundamental concepts, algorithms, and implementation techniques for machine learning models.

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

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Awesome Machine Learning Education GitHub Repositories

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  • 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

    Explores development patterns for orchestrating complex workflows using language model integration libraries.

    JavaScriptcsscurriculumeducation
  • 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

    Explains fundamental concepts, algorithms, and implementation techniques required for building and deploying machine learning models.

    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

    Unpacks the mechanisms behind transformer-based models for interpreting complex text data through structured 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

    Offers practical documentation for building, fine-tuning, and deploying modern language models.

    courselarge-language-modelsllm
  • Developer-Y/cs-video-courses

    Developer-Y/cs-video-courses

    74,064GitHubView on GitHub↗

    This project is a community-driven educational repository that serves as a comprehensive directory of university-level computer science video lectures. It provides a structured learning path for students and professionals, aggregating high-quality academic resources to facilitate self-paced study across a wide range of

    Assembles academic video resources explaining how to derive insights from unlabeled datasets.

    algorithmsbioinformaticscomputational-biology
  • tensorflow/tfjs-examples

    tensorflow/tfjs-examples

    6,783GitHubView on GitHub↗

    This repository provides a collection of practical demonstrations and implementation guides for machine learning tasks using TensorFlow.js. It serves as a resource for developers to explore model architectures, training workflows, and data manipulation techniques across domains such as computer vision, natural language

    Educational examples illustrate the implementation of generative adversarial network architectures, including associated input types and task-specific logic.

    JavaScript

Explore sub-tags

  • Batch NormalizationTechniques for stabilizing neural network training by normalizing layer inputs.
  • Computational Performance OptimizationTechniques for improving training and inference speed in deep learning.
  • Computer Vision ProjectsPractical implementations and guided exercises focused on image processing and deep learning applications.
Convolutional Neural Network Architectures
Historical and modern neural network architectures used in computer vision tasks.
  • Generative Adversarial NetworksExamples and implementations of GAN architectures.
  • LLM Engineering Guides3 sub-tagsPractical documentation and implementation strategies for building, fine-tuning, and deploying large language models.
  • Large Language Model ArchitecturesFoundational concepts and structural components of transformer-based models.
  • Large Language Model Pre-trainingInstructional materials covering the methodologies, data requirements, and computational processes for pre-training large language models.
  • Learning Rate SchedulersAlgorithms that adjust the learning rate during training to improve convergence and model performance.
  • Sentiment Analysis ModelsImplementations of neural network architectures for classifying text sentiment.
  • Softmax RegressionImplementation and theory of softmax regression models for multi-class classification.
  • Unsupervised LearningEducational content focused on machine learning algorithms that identify patterns in unlabeled data.