Learning & reference for beginner learners
119 resources · page 4 of 4
Datawhale leedl-tutorial 李宏毅深度学习教程 (苹果书)
by Datawhale
Datawhale's Chinese deep-learning tutorial based on Hung-yi Lee's lectures, with a free PDF.
Datawhale so-large-lm 大模型基础
by Datawhale
Datawhale so-large-lm GitHub repo: Chinese course on LLM fundamentals based on Stanford CS324 and Hung-yi Lee's lectures.
DeepLearning.AI short courses
DeepLearning.AI short courses catalogue: one- to two-hour courses on LLM applications, agents, fine-tuning and RAG.
Dive into Deep Learning
by Aston Zhang, Zachary C. Lipton, Mu Li and Alexander J. Smola
Dive into Deep Learning: free interactive textbook with maths and runnable code in PyTorch, JAX, TensorFlow and MXNet.
动手学深度学习
by Aston Zhang, Zachary C. Lipton, Mu Li and Alexander J. Smola
Chinese edition of Dive into Deep Learning with text, maths and runnable code.
Google Flood Hub / Flood Forecasting
Google Flood Hub: real-time ML riverine flood forecasts, including for data-scarce regions.
Harvard CS50 AI
Harvard CS50 AI: free introductory course on search, knowledge, optimisation, machine learning and neural networks in Python.
Hugging Face LLM Course
by Hugging Face
Hugging Face LLM Course: free course on transformers, datasets, tokenizers, fine-tuning and reasoning models.
Hung-yi Lee course index (NTU)
by Hung-yi Lee (National Taiwan University)
Hung-yi Lee's NTU homepage indexing all his machine learning and generative AI courses since 2015.
Hung-yi Lee GenAI-ML 2025 Fall
by Hung-yi Lee (National Taiwan University)
Hung-yi Lee's Introduction to GenAI and ML (Fall 2025) course page at National Taiwan University.
Illustrated Transformer (Alammar)
by Jay Alammar
Jay Alammar's Illustrated Transformer: visual explanation of attention and the transformer architecture.
Speech and Language Processing (Jurafsky & Martin)
by Dan Jurafsky and James H. Martin (Stanford University)
Free draft of Jurafsky and Martin's Speech and Language Processing, 3rd edition, covering NLP and LLMs.
LLM Visualization (bbycroft)
LLM Visualization by Brendan Bycroft: interactive 3D walkthrough of GPT-style inference step by step.
Microsoft 2025 Work Trend Index: the "Frontier Firm"
by Microsoft
Microsoft 2025 Work Trend Index feature on the Frontier Firm: survey data on AI agents and workforce change.
Microsoft Generative AI for Beginners
by Microsoft
Microsoft Generative AI for Beginners GitHub repo: 21 lessons with code on building generative AI applications.
Seeing AI
Microsoft Seeing AI: free app that narrates text, people and surroundings for blind and low-vision users.
mlcourse.ai
by Yury Kashnitsky (mlcourse.ai)
mlcourse.ai: open machine learning course from the Open Data Science community, self-paced with assignments.
ModelScope
ModelScope: Alibaba's hub of open models, datasets and demos, with Chinese tutorials.
ODS.ai course tracks
Open Data Science course tracks: Russian-language courses on NLP, LLMs, MLOps and other ML topics.
Prompt Engineering Guide (DAIR.AI)
by DAIR.AI
DAIR.AI Prompt Engineering Guide: overview of prompting techniques, applications and model notes, in many languages.
Transformer Explainer (Georgia Tech)
by Polo Club of Data Science, Georgia Tech
Georgia Tech Transformer Explainer: interactive in-browser visualisation of how a GPT-2 transformer works.
Transkribus Help Center
Transkribus Help Center: guides to training and applying handwriting-recognition models on documents.
Учебник по машинному обучению / YSDA ML textbook
by Yandex School of Data Analysis
Yandex School of Data Analysis ML textbook in Russian, from basic algorithms to current research, with maths and code.