4 repository-uri
Awesome GitHub RepositoriesMachine Learning Tutorials
Educational content and practical implementations of machine learning models.
Distinguishing note: Focuses on learning and implementation rather than production ML frameworks.
Explore 4 awesome GitHub repositories matching artificial intelligence & ml · Machine Learning Tutorials. Refine with filters or upvote what's useful.
Awesome Machine Learning Tutorials GitHub Repositories
Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
- tangyudi/ai-learn
tangyudi/Ai-Learn
13,065Vezi pe GitHubAi-Learn is an educational repository and technical reference designed to facilitate the mastery of artificial intelligence and data science workflows. It provides a structured curriculum that combines theoretical mathematical foundations with practical coding exercises, enabling users to build predictive models, neural networks, and analytical pipelines using Python. The project distinguishes itself by emphasizing a first-principles approach to machine learning. Rather than relying solely on high-level abstractions, it guides users through the reconstruction of core algorithms from scratch,
Offers structured tutorials and code implementations for learning machine learning and deep learning.
algorithmartificial-intelligencecaffe - morvanzhou/tutorials
MorvanZhou/tutorials
12,952Vezi pe GitHubThis repository is a comprehensive collection of instructional guides and practical examples for Python development, focusing on machine learning, data science, and web scraping. It provides implementations for neural networks, reinforcement learning algorithms, and deep learning architectures using PyTorch, alongside detailed manuals for scientific computing and data visualization. The project distinguishes itself by offering specialized tutorials on concurrent programming to optimize CPU performance and guides for setting up Linux development environments. It covers the implementation of ad
Provides educational content and practical implementations of neural networks and reinforcement learning algorithms.
Pythonmachine-learningmultiprocessingneural-network - probml/pyprobml
probml/pyprobml
7,096Vezi pe GitHubpyprobml is a collection of notebook-based implementations of probabilistic machine learning models and algorithms. It uses scientific computing and data analysis libraries to execute mathematical concepts and theories for practical application and research. The project focuses on the programmatic generation of scientific figures and visualizations to recreate results from a technical text. It employs a system of branch-based asset storage to isolate these generated images from the source code. The repository covers a wide range of probabilistic modeling and machine learning tasks, including
Provides pedagogical notebooks that guide users through the implementation of machine learning models using scientific libraries.
Jupyter Notebookblackjaxcolabflax - dragen1860/tensorflow-2.x-tutorials
dragen1860/TensorFlow-2.x-Tutorials
6,351Vezi pe GitHubThis project is a collection of TensorFlow 2.x machine learning tutorials and practical code examples. It serves as a deep learning implementation guide for constructing diverse neural network architectures, including convolutional, recurrent, and generative networks. The repository provides templates and examples for several specialized domains, including computer vision for image classification and object detection, natural language processing for text generation and language understanding, and generative AI for synthesizing data using adversarial networks and autoencoders. It also includes
Provides educational content and practical implementations of machine learning models using TensorFlow 2.x.
Jupyter Notebookartificial-intelligencecomputer-visiondeep-learning
