If you already have 200 open tabs with courses, articles, and GitHub repositories on ML, this repository might save the situation a bit. 😅 Awesome Machine Learning Resources is a huge collection of sub-collections on machine learning, deep learning, and AI. 🤖 Instead of endless Google searches, everything is organized into categories: • fundamentals of machine learning • neural networks and modern architectures • tasks and application areas • datasets • libraries and tools • fairness and AI ethics • production ML and MLOps Each link has a short description, so you can quickly understand whether it's worth opening it or skipping it. 📝 I particularly liked that the authors mark abandoned collections with an icon if they haven't been updated in over a year. ⚠️ 🌐 https://github.com/ZhiningLiu1998/awesome-machine-learning-resources
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