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Machine Learning Mastery
A curated collection of notes for CS majors and passionate learners, bridging the gap between fundamental algorithms and modern artificial intelligence.
🌟 Main Contributors
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Jue Guo Lead Author Personal Website Jue (Bob) Guo is a Ph.D. candidate and adjunct professor in Computer Science at the University at Buffalo, specializing in machine learning, deep learning and AI. He translates complex theory into practical projects with PyTorch and TensorFlow, develops curricula and mentors students bridging classical algorithms with modern AI techniques.
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Kristopher Kodweis Lead Author LinkedIn As a M.S. candidate in Mechanical Engineering, Kristopher Kodweis engineers intelligent computer vision systems for mobile platforms. His approach is shaped by a background in visual communication design, photography, and woodworking, focusing on innate human-centered principles. Kristopher creates technology that is robust and intuitive, aiming for AI tools that are seamless extensions of human capability.
🚀 Help Build This Resource
This project is built by the community. From fixing a typo to adding notes on a new research paper, all contributions are welcome. See an area for improvement? Feel free to open an issue on GitHub or join our community on Slack to discuss ideas.