Learning & reference for intermediate learners
139 resources · page 4 of 5
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.
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.
CatBoost documentation
CatBoost documentation: Yandex's open-source gradient boosting library with native handling of categorical features.
CFA Institute: AI in Asset Management report 2025
CFA Institute press release on its 2025 report about AI adoption in asset management.
CMU 11-667 LLMs: Methods & Applications
CMU 11-667 course site: graduate course on large language model methods and applications, with schedule and materials.
Decree of the President of the Russian Federation on the Development of AI (CSET translation)
by Center for Security and Emerging Technology
CSET English translation of Russia's 2019 presidential decree on the development of artificial intelligence.
Darts
by Unit8 SA
Darts documentation: Python library for time-series forecasting and anomaly detection with backtesting.
eScriptorium
by eScriptorium project (EPHE, PSL)
eScriptorium documentation: open platform for transcribing and annotating historical documents with OCR and HTR.
EU AI Act Art.3 definitions
EU AI Act Article 3 text: the legal definitions used throughout the regulation, such as AI system and provider.
girafe-ai ML course
by girafe.ai
girafe-ai ml-course GitHub repo: open machine learning course with lecture materials and assignments, in Russian.
Goodfellow et al., Deep Learning
by Ian Goodfellow, Yoshua Bengio and Aaron Courville
Author site for the Deep Learning textbook by Goodfellow, Bengio and Courville, free to read online.
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.