The online resources/tutorials to learn AI. ⭐ represents importance. 💥 represents difficulty
- Educative Grokking the Machine Learning Interview ⭐⭐⭐ 💥
- Educative Machine Learning System Design ⭐⭐⭐ 💥
- Systems Design Interview Guide ⭐⭐ 💥
- machine-learning-interviews ⭐⭐ 💥💥
- machine-learning-interview ⭐⭐ 💥
- Landmark Papers in Machine Learning ⭐ 💥
- Papers on Explainable Artificial Intelligence ⭐ 💥
- Must-read papers on GNN ⭐ 💥
- Cracking the Data Science Interview ⭐⭐⭐ 💥
- Machine Learning Design Patterns ⭐⭐ 💥💥
- Designing Machine Learning Systems ⭐⭐ 💥💥
- Probability cheatsheet ⭐⭐ 💥
- Statistics cheatsheet ⭐⭐ 💥
- Linear algebra explained in four pages ⭐⭐ 💥
- Calculus Cheat Sheet ⭐⭐ 💥
- probability_cheatsheet v2 ⭐⭐ 💥
- mathematics-for-machine-learning -- Andrew Ng ⭐⭐ 💥💥
- Math for ML -- Tübingen Machine Learning ⭐ 💥💥💥
- Math for DL -- Tübingen Machine Learning ⭐ 💥💥💥
- Prompt Engineering Guide ⭐⭐ 💥
- Google Tuning Playbook ⭐⭐⭐ 💥💥
- Intermediate Python ⭐⭐⭐ 💥💥
- Approaching (Almost) Any Machine Learning Problem ⭐⭐ 💥
- Everything about Distributed Training and Efficient Finetuning ⭐⭐ 💥
- Datasets and Benchmarks Best Practices ⭐
- Optuna ⭐⭐ 💥
- Dive into Deeplearning ⭐⭐⭐ 💥
- Annotated Research Paper Implementations ⭐⭐ 💥💥
- Grokking the Machine Learning Interview ⭐⭐⭐ 💥
- Machine Learning System Design ⭐⭐⭐ 💥
- Practical Deep Learning ⭐⭐⭐ 💥
- Stanford CS 221 ― Artificial Intelligence ⭐⭐ 💥💥
- Stanford CS 230 ― Deep Learning ⭐⭐ 💥💥
- Serrano Academy ⭐⭐⭐ 💥
- ML CheatSheets ⭐
- Google ML Course ⭐⭐ 💥
- SuperVIP Cheatsheet: Machine Learning ⭐ 💥
- Stanford CS 229 ― Machine Learning ⭐⭐ 💥💥
- StatQuest with Josh Starmer ⭐⭐ 💥
- Practical NLP with Python ⭐ 💥
- Hugging Face NLP Course ⭐⭐ 💥
- NLP CheatSheet: Master NLP ⭐
- ML CHEATSHEET: A mind map for NLP ⭐
- Metric Learning ⭐ 💥
- Git Tutorial ⭐⭐ 💥
- CS 329S: Machine Learning Systems Design ⭐⭐ 💥💥
- Grokking the Machine Learning Interview ⭐⭐⭐ 💥
- ML System Design Pattern ⭐⭐ 💥💥