rohitg00 / ai-engineering-from-scratch
A free, MIT-licensed course of 542 lessons on AI engineering, implementing model internals, retrieval, and agent runtimes from scratch.
rohitg00 / ai-engineering-from-scratch
ashishps1 / awesome-system-design-resources
A curated list of free system design learning materials and interview preparation problems and concepts.
byoungd / up
An open, bilingual Chinese-language book-guide on lifelong learning in the AI era, covering English study, AI learning, real projects, and personal recovery.
mrdbourke / zero-to-mastery-ml
Course materials, code, notebooks and datasets for the Zero to Mastery Machine Learning and Data Science course.
yvoronoy / awesome-english
A curated list of resources for learning English across listening, speaking, reading, writing, grammar, and vocabulary.
NirDiamant / RAG_Techniques
A collection of 42+ runnable Jupyter notebooks, each tutorial covering an advanced technique for Retrieval-Augmented Generation systems.
google-research / google-research
Monorepo of research code and datasets released by Google Research, spanning many subprojects.
microsoft / AI-For-Beginners
A 12-week, 24-lesson beginner curriculum covering AI fundamentals, neural networks, computer vision, NLP, and AI ethics with TensorFlow and PyTorch labs.
alirezadir / AIMLInterviews
A study guide and interview-prep curriculum for AI/ML technical roles at big tech, covering coding, ML breadth, system design, and behavioral rounds.
microsoft / ML-For-Beginners
A 12-week, 26-lesson beginner curriculum on classic machine learning using Scikit-learn, with quizzes and projects in Python and R.
xiaolai / the-craft-of-selfteaching
A Chinese-language book by Li Xiaolai teaching self-learning skills through a Python programming curriculum, delivered as Jupyter notebooks.
DataTalksClub / machine-learning-zoomcamp
A free, cohort-based course teaching ML engineering: training models, exposing them via APIs, and deploying with Docker, Kubernetes, and AWS Lambda.
exacity / deeplearningbook-chinese
Chinese translation of the Deep Learning textbook by Goodfellow, Bengio, and Courville, with community proofreading.