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Post A new collection of free courses has been added:

3 June 2026
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Machine Learning with Python
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A new collection of free courses has been added: 🔗 https://github.com/dair-ai/ML-Course-Notes Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. 📚 Machine Learning Course Notes is an open collection of notes on machine learning, NLP, and AI, compiled around full-fledged courses, not just individual videos. 🧠 What's inside: • Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others • A table with lectures, descriptions, videos, notes, and authors • Links to the original lectures and accompanying notes • WIP markers for incomplete materials • Instructions for contributors on adding and improving notes The idea was appreciated. 👍 Instead of another collection of hundreds of links, a course map has been created where one can systematically go through the material without getting lost after a week of studying. 🗺️ #MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A 🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more. ✅ 13 courses live + 40+ coming soon 🎯 One access, lifetime updates 🔑 Use code: PRESALE-BOOK-WAVE-2GFG 👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
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MMachine Learning with PythonJoin our livestream with Marina Wyss, Senior Applied Scientist at Twitch, as we discuss how to break into AI Engineering in 2026. Sign up for FREE and save yourMMachine Learning with Python5 Fun Papers That Explain LLMs Clearly 📚✨ Want to understand LLMs better? Start with these five foundational papers that explain how they work. 🤖 Large language
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