Learning & reference
Learning & reference
- academic venues & institutes (26)
- courses & textbooks (30)
- definitions & canon (18)
- discovery & reports (81)
- practice guides (best/worst) (22)
177 resources · page 5 of 6
Google ML Glossary
by Google
Google Machine Learning Glossary defining ML terms, including TensorFlow and large language model terminology.
Habr ML hub
by Habr
Habr machine learning hub: Russian-language articles on ML from practitioners and companies.
Happy-LLM
by Datawhale
Datawhale Happy-LLM GitHub repo: Chinese tutorial on building an LLM from scratch, covering tokenizer, pretraining, SFT, LoRA, RAG and agents.
HF Transformers glossary
by Hugging Face
Hugging Face Transformers glossary defining terms used in transformer models and the library.
HSE CS wiki
by HSE University Faculty of Computer Science
HSE Faculty of Computer Science wiki with course pages for machine learning and deep learning, in Russian.
Hung-yi Lee ML 2025 Spring
by Hung-yi Lee (National Taiwan University)
Hung-yi Lee's ML 2025 Spring course page: agents, LLM internals, Mamba, post-training, reasoning and model editing.
Hung-yi Lee ML 2026 Spring
by Hung-yi Lee (National Taiwan University)
Hung-yi Lee's ML 2026 Spring course page at National Taiwan University with lectures and assignments.
Learning in the Open: What AI Is and Isn't Changing (Khan Academy)
by Khan Academy
Khan Academy post on lessons from deploying the Khanmigo AI tutor: what works and what does not.
Letta docs
by Letta
Letta documentation: platform for building stateful agents with persistent memory, successor to MemGPT.
Llama Guard
arXiv paper (2023) introducing Llama Guard, an LLM-based classifier for safeguarding human–AI conversation inputs and outputs.
Made With ML
by Goku Mohandas (Made With ML, Anyscale)
Made With ML by Anyscale: course on designing, developing, deploying and iterating on production ML applications.
MemGPT
by Charles Packer et al. (UC Berkeley)
arXiv paper (2023) introducing MemGPT, OS-style virtual context management for LLM agents.
ML-Ops.org
ML-Ops.org: reference on MLOps principles and practices for operationalising machine-learning models.
Murphy, Probabilistic ML
by Probabilistic machine learning
Kevin Murphy's Probabilistic Machine Learning book series site, with free introductory and advanced volumes.
NIST AI 600-1 GenAI Profile
by NIST
NIST AI 600-1 PDF: Generative AI Profile of the AI RMF listing 12 GenAI-specific risks and suggested actions.
NIST AI glossary
by NIST
NIST AI Resource Center glossary of trustworthy-AI terms from the AI Risk Management Framework, with references.
NIST AI Risk Management Framework
by NIST
NIST AI Risk Management Framework page: the Govern, Map, Measure and Manage framework with resources.
OECD AI Principles & AI system definition
by OECD
OECD.AI page on the OECD AI Principles and the OECD definition of an AI system.
Prince, Understanding Deep Learning
by udlbook
Simon Prince's Understanding Deep Learning textbook site with free PDF and Python notebooks.
Second RIBA AI Report shows surge in usage among UK architects
by Royal Institute of British Architects (RIBA)
RIBA news release on its second AI report, showing rising AI use among UK architects.
Russell & Norvig AIMA
by Stuart Russell and Peter Norvig
Author site for Russell and Norvig's Artificial Intelligence: A Modern Approach, with code, exercises and resources.
Stanford CS229
Stanford CS229 Machine Learning course site with lecture notes on learning algorithms and statistical foundations.
Stanford CS25 Transformers United V6
Stanford CS25 Transformers United V6 seminar site with talks by researchers on transformer research.
The Convergence of AI and Creativity: Introducing Ghostwriter (Ubisoft)
by Ubisoft
Ubisoft post introducing Ghostwriter, an in-house AI tool that drafts NPC dialogue barks for writers.
UK Government AI Playbook
by Government Digital Service (UK Government)
AI Playbook for the UK Government: principles and guidance for civil servants on using AI safely, including procurement.
UNESCO guidance for generative AI in education and research
by UNESCO
UNESCO guidance on generative AI in education and research for governments and institutions.
Why Do Multi-Agent LLM Systems Fail?
by Mert Cemri et al. (UC Berkeley)
arXiv paper (2025) analysing why multi-agent LLM systems fail, with a taxonomy of 14 failure modes.
Wikipedia: Large language model
by Wikipedia (Wikimedia Foundation)
Wikipedia article on large language models: definition, history, architecture, training and limitations.
Yandex ML Handbook (Учебник по машинному обучению)
Yandex School of Data Analysis machine learning handbook in Russian, from classical algorithms to deep learning theory, with maths and code.
YSDA NLP course
by Yandex School of Data Analysis
YSDA nlp_course GitHub repo: natural-language-processing course from Yandex School of Data Analysis with lectures and notebooks.
arXiv cs.AI recent
arXiv listing of recent papers in the cs.AI (Artificial Intelligence) category.
Attention Is All You Need
by Ashish Vaswani et al. (Google)
arXiv paper (2017) "Attention Is All You Need", introducing the Transformer architecture.