Foundations
Understand language models and choose a learning path.
- Llm Fundamentals (139)
- Courses And Learning Paths (179)
- From Scratch Implementations (1)
- Practitioner Overviews (387)
706 resources · page 19 of 23
Hugging Face LLM Course
by Hugging Face
A structured route through the Hugging Face ecosystem.
Hung-yi Lee ML 2025 Spring
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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
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Hung-yi Lee's ML 2026 Spring course page at National Taiwan University with lectures and assignments.
ChinAI Newsletter (Jeffrey Ding)
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Jeffrey Ding's ChinAI newsletter: weekly English translations of Chinese writing on China's AI landscape.
Karpathy: Unreasonable Effectiveness of RNNs
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Andrej Karpathy's 2015 essay The Unreasonable Effectiveness of Recurrent Neural Networks, with char-RNN examples.
Learning in the Open: What AI Is and Isn't Changing (Khan Academy)
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Khan Academy post on lessons from deploying the Khanmigo AI tutor: what works and what does not.
Letta docs
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Letta documentation: platform for building stateful agents with persistent memory, successor to MemGPT.
LightGBM documentation
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LightGBM documentation: gradient boosting framework with tree-based learning, tuning guides and distributed training.
Llama Guard
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arXiv paper (2023) introducing Llama Guard, an LLM-based classifier for safeguarding human–AI conversation inputs and outputs.
Recurrent Neural Networks and LSTM (Jürgen Schmidhuber)
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Jürgen Schmidhuber's IDSIA page on recurrent neural networks and LSTM, with history and references.
Made With ML
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Made With ML by Anyscale: course on designing, developing, deploying and iterating on production ML applications.
MemGPT
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arXiv paper (2023) introducing MemGPT, OS-style virtual context management for LLM agents.
ML-Ops.org
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ML-Ops.org: reference on MLOps principles and practices for operationalising machine-learning models.
Murphy, Probabilistic ML
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Kevin Murphy's Probabilistic Machine Learning book series site, with free introductory and advanced volumes.
NIST AI 600-1 GenAI Profile
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NIST AI 600-1 PDF: Generative AI Profile of the AI RMF listing 12 GenAI-specific risks and suggested actions.
NIST AI glossary
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NIST AI Resource Center glossary of trustworthy-AI terms from the AI Risk Management Framework, with references.
NIST AI Risk Management Framework
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NIST AI Risk Management Framework page: the Govern, Map, Measure and Manage framework with resources.
NN/g: Artificial Intelligence topic hub
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Nielsen Norman Group AI topic hub: UX research articles, videos and courses on designing with and for AI.
npaka
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npaka's note.com blog: Japanese-language how-to articles on LLM APIs, frameworks and new AI tools.
NYU Deep Learning (LeCun/Canziani)
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NYU Deep Learning course (Spring 2021) by Yann LeCun and Alfredo Canziani, with lectures, labs and notebooks.
OECD AI Principles & AI system definition
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OECD.AI page on the OECD AI Principles and the OECD definition of an AI system.
OECD AI Recommendation (OECD-LEGAL-0449)
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OECD Recommendation of the Council on Artificial Intelligence, the source of the OECD AI Principles and AI system definition.
PDE-Transformer
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PDE-Transformer project page: transformer architecture for learning partial differential equations from data.
Physics-based Deep Learning (TUM)
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Physics-based Deep Learning book from TUM: hands-on guide to combining physical simulation with deep learning.
PointNet
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PointNet project page: deep network architecture that consumes raw point clouds for 3D classification and segmentation.
Prince, Understanding Deep Learning
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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
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RIBA news release on its second AI report, showing rising AI use among UK architects.
Roboflow documentation
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Roboflow documentation for building computer-vision datasets, training models and deploying them.
Russell & Norvig AIMA
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Author site for Russell and Norvig's Artificial Intelligence: A Modern Approach, with code, exercises and resources.
Sarah Guo (@saranormous)
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No Priors podcast YouTube channel (Sarah Guo and Elad Gil): interviews with AI founders and researchers.
Sean Grove (@sgrove)
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AI Engineer YouTube channel: conference talks, such as Sean Grove's The New Code on specs as the primary artifact.
LLMs-from-scratch (book code)
Follow a GPT implementation rather than treating the model as a black box.