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Source channel @githubtrending · Post #14869 · Jun 26

#html#data_science#education#machine_learning#machine_learning_algorithms#machinelearning#machinelearning_python#microsoft_for_beginners#ml#python#r#scikit_learn#scikit_learn_python Microsoft’s "Machine Learning for Beginners" is a free, 12-week course with 26 lessons designed to teach classic machine learning using Python and Scikit-learn. It includes quizzes, projects, and assignments to help you learn by doing, with lessons themed around global cultures to keep it engaging. You can access solutions, videos, and even R language versions. The course is beginner-friendly, flexible, and helps build practical skills step-by-step, making it easier to understand and apply machine learning concepts in real-world scenarios. This structured approach boosts your learning retention and prepares you for further study or career growth in ML[1][5]. https://github.com/microsoft/ML-For-Beginners

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@githubtrending · Post #15518 · 02/24/2026, 11:30 AM

#rust#ai#ai_ocr#attention_mechanism#gnn#gnn_model#gnns#graph#graph_neural_networks#llm_inference#low_latency#mincut#neo4j#ocr#onnx#rust#vector#wasm RuVector is a free, open-source vector database that gets smarter with every query. Unlike static databases, it learns from usage via GNN layers, runs LLMs locally with no cloud costs, supports graph queries like Neo4j, scales freely across nodes, and deploys as a single self-booting file (125ms startup). Run with `npx ruvector`. You benefit from faster, more accurate AI search that improves automatically, zero operating costs, full offline/privacy control, and easy scaling—perfect for RAG, agents, or edge apps without vendor lock-in. https://github.com/ruvnet/ruvector