Artificial Intelligence
76 items from owainlewis/awesome-artificial-intelligence ★16,638
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12-Factor Agents github.com
Practical principles for building controllable LLM applications around deterministic software.
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OpenAI Evals github.com
An open-source framework and registry for evaluating language models and systems.
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Neo github.com
An open-source, workflow-first terminal coding agent with subagents, skills, sandboxed tools, and multiple model providers.
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Continue continue.dev
Open-source AI code assistant. Connect any model and any context to create custom autocomplete and chat experiences inside the IDE. #opensource
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aider aider.chat
AI pair programming in your terminal, supporting multiple LLM providers. #opensource
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Deep Learning deeplearningbook.org
Yet halfway through the book, it contains satisfying math content on how to think about actual deep learning.
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Deep Learning: Foundations and Concepts bishopbook.com
A probability-grounded treatment by Christopher and Hugh Bishop.
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Effective Context Engineering for AI Agents anthropic.com
How to select, structure, and manage the context available to long-running agents.
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Building Effective Agents anthropic.com
Anthropic's practical patterns and tradeoffs for agentic systems.
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Build a Large Language Model (From Scratch) manning.com
A guide to building your own working LLM, by Sebastian Raschka.
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Claude Code code.claude.com
Anthropic's agentic coding tool that lives in your terminal and helps you turn ideas into code.
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Attention Is All You Need arxiv.org
(AIAYN) - Introducing multi-head self-attention neural networks with positional encoding to do sentence-level NLP without any RNN nor CNN - this paper is a must-read (also see this explanation and this visualization of the paper).
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fast.ai - Practical Deep Learning For Coders course.fast.ai
A code-first introduction to deep learning.
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Machine Learning Bookcamp manning.com
A project-based introduction to building and deploying machine learning systems by Alexey Grigorev.
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Karpathy's Neural Networks: Zero to Hero youtube.com
Build neural networks and language models from first principles.
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Speech and Language Processing web.stanford.edu
The continuously updated NLP reference by Dan Jurafsky and James Martin.
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Reinforcement Learning: An Introduction web.stanford.edu
Sutton and Barto's foundational treatment of reinforcement learning concepts and algorithms.
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Understanding Deep Learning udlbook.github.io
Theory, intuition, and practical notebooks by Simon Prince.
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Promptfoo promptfoo.dev
Test cases, assertions, model comparisons, and red-team checks for LLM applications.
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Designing Machine Learning Systems oreilly.com
Scalable, maintainable machine learning systems by Chip Huyen.
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Running Agents openai.github.io
Lifecycle, session, exception, and durable-execution patterns in the OpenAI Agents SDK.
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Human-in-the-Loop openai.github.io
Pause, inspect, approve, reject, and resume tool calls without losing agent state.
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