Curated AI Resources
Hand-picked datasets, courses, newsletters, communities, and developer tools for AI builders and learners.
56 resources curated
Featured Resources
Fast.ai Practical Deep Learning
Free, practical deep learning course by Jeremy Howard and Rachel Thomas. Teaches cutting-edge deep learning techniques using top-down, code-first methodology. Covers computer vision, NLP, tabular data, and collaborative filtering using PyTorch and the fastai library.
Hugging Face NLP Course
Free, hands-on NLP course from Hugging Face covering transformers, BERT, GPT, fine-tuning, and the full Hugging Face ecosystem — Datasets, Tokenizers, Accelerate, and PEFT. Ideal for developers wanting to work with state-of-the-art language models.
Hugging Face Datasets Hub
The largest open-source hub for machine learning datasets with 200,000+ datasets across NLP, computer vision, audio, tabular, and multimodal tasks. Browse, preview, and load datasets directly into your training pipeline using the datasets Python library with a single line of code.
Kaggle Datasets
Kaggle hosts 250,000+ public datasets across data science, machine learning, computer vision, NLP, and domain-specific fields. Datasets include structured tabular data, images, text corpora, time series, and more. Integrated with Kaggle Notebooks for immediate analysis.
The Rundown AI
The most widely read AI newsletter with 700,000+ subscribers. Delivers a daily digest of the most important AI news, tool launches, research papers, and industry moves in under 5 minutes. Clear, jargon-free summaries make it ideal for staying current without information overload.
DeepLearning.AI Specializations
Andrew Ng's comprehensive AI education platform offering specializations in deep learning, MLOps, NLP, and generative AI. Courses are project-driven, covering neural networks, CNNs, RNNs, transformers, and production ML systems. Trusted by 7 million+ learners worldwide.
All Resources
The Rundown AI
The most widely read AI newsletter with 700,000+ subscribers. Delivers a daily digest of the most important AI news, tool launches, research papers, and industry moves in under 5 minutes. Clear, jargon-free summaries make it ideal for staying current without information overload.
Fast.ai Practical Deep Learning
Free, practical deep learning course by Jeremy Howard and Rachel Thomas. Teaches cutting-edge deep learning techniques using top-down, code-first methodology. Covers computer vision, NLP, tabular data, and collaborative filtering using PyTorch and the fastai library.
Hugging Face NLP Course
Free, hands-on NLP course from Hugging Face covering transformers, BERT, GPT, fine-tuning, and the full Hugging Face ecosystem — Datasets, Tokenizers, Accelerate, and PEFT. Ideal for developers wanting to work with state-of-the-art language models.
Hugging Face Datasets Hub
The largest open-source hub for machine learning datasets with 200,000+ datasets across NLP, computer vision, audio, tabular, and multimodal tasks. Browse, preview, and load datasets directly into your training pipeline using the datasets Python library with a single line of code.
Kaggle Datasets
Kaggle hosts 250,000+ public datasets across data science, machine learning, computer vision, NLP, and domain-specific fields. Datasets include structured tabular data, images, text corpora, time series, and more. Integrated with Kaggle Notebooks for immediate analysis.
DeepLearning.AI Specializations
Andrew Ng's comprehensive AI education platform offering specializations in deep learning, MLOps, NLP, and generative AI. Courses are project-driven, covering neural networks, CNNs, RNNs, transformers, and production ML systems. Trusted by 7 million+ learners worldwide.
Ben's Bites
Daily AI newsletter by Ben Tossell covering the latest AI products, research, and tools. Known for its approachable, conversational tone and comprehensive coverage of everything happening in the AI ecosystem — from startup launches to paper summaries.
The Batch — DeepLearning.AI
Weekly AI newsletter from Andrew Ng and DeepLearning.AI. Covers AI research breakthroughs, business applications, policy, and societal impact with depth and insight. Includes Andrew Ng's editorial on the state of AI. Required reading for serious AI practitioners.
Hugging Face Community
The largest open-source AI community on the web. The Hugging Face Hub hosts models, datasets, and Spaces for the global ML community. Forums, discussion threads on model pages, and the Hub social feed enable collaboration among 500,000+ ML practitioners and researchers.
Reddit r/MachineLearning
The largest ML community on Reddit with 3 million+ members. Covers research paper discussions, career advice, project showcases, and industry news. Home to iconic AMAs with AI researchers and daily discussion threads on arXiv papers. High signal-to-noise for serious practitioners.
LangChain
The most widely used framework for building LLM-powered applications. LangChain provides abstractions for chains, agents, RAG pipelines, tool integrations, and memory. Supports Python and JavaScript. 90,000+ GitHub stars, 2,000+ integrations, and a huge ecosystem of extensions.
CrewAI
Open-source framework for orchestrating role-based multi-agent AI systems. CrewAI lets you create teams of AI agents with distinct roles, goals, and tools that collaborate to complete complex tasks. Python-native, clean API, and the fastest-growing agentic framework in 2024–2025.
Ollama
Run large language models locally with a single command. Ollama provides a simple CLI and REST API for running Llama 3, Mistral, Gemma, Phi, and 100+ other models on your Mac, Linux, or Windows machine. No cloud required, full privacy, OpenAI-compatible API.
OpenAI API
OpenAI's REST API provides access to GPT-4o, o3, DALL-E 3, Whisper, TTS, and Embeddings models. Features include Assistants API with tool use, Batch API for async workloads, fine-tuning, and structured outputs. The most widely used AI API with SDKs for Python, Node.js, and more.
Anthropic Claude API
Anthropic's API for Claude — the leading AI assistant for complex reasoning, coding, analysis, and long-context tasks. Supports 200k token context window, tool use, vision, and the Model Context Protocol (MCP). Offers Claude 3.5 Sonnet, Claude 3 Opus, and Haiku variants.
Andrej Karpathy — Neural Networks: Zero to Hero
Andrej Karpathy's legendary YouTube series building neural networks from scratch in pure Python, culminating in implementing GPT-2. The clearest, most rigorous free resource for understanding how LLMs actually work internally. Essential viewing for any serious AI practitioner.
Anthropic Prompt Engineering Guide
Anthropic's official, comprehensive guide to prompt engineering for Claude. Covers system prompts, chain-of-thought, structured outputs, XML formatting, role assignment, and advanced techniques like constitutional AI. Written by the team that builds and trains Claude.
arXiv cs.AI & cs.LG
arXiv is the primary preprint server where virtually all AI and ML research is published before (and often instead of) peer review. The cs.AI (Artificial Intelligence) and cs.LG (Machine Learning) categories receive 50–100+ new papers daily. The heartbeat of the AI research community.
Papers With Code
The definitive resource for tracking state-of-the-art ML research with linked code implementations. Browse benchmark leaderboards across NLP, computer vision, RL, and more. Each paper entry links to GitHub repositories, making it easy to reproduce and build on research.
Superhuman AI
Newsletter focused on practical AI productivity — how to use AI tools like ChatGPT, Claude, and Midjourney to save time and work smarter. Covers workflows, prompt templates, and tool comparisons. Targeted at professionals integrating AI into their daily work.
AlphaSignal
Weekly digest of the most important AI research papers and model releases, curated by ML practitioners. AlphaSignal highlights breakthroughs across NLP, vision, RL, and reasoning, with brief plain-English summaries linking to original papers and code.
Lilian Weng's Blog
Lilian Weng's personal blog is arguably the most respected source of technical deep-dives on AI research. The OpenAI VP covers transformers, diffusion models, RL, agents, LLM alignment, and more with extraordinary clarity and depth. Each post is a masterclass in explaining complex AI concepts.
Distill.pub
Distill is a scientific journal dedicated to clear, interactive explanations of machine learning research. Articles use interactive visualisations to explain complex concepts like attention mechanisms, feature visualisation, and neural network interpretability. Highest-quality AI explanations on the web.
Discord — Midjourney
The Midjourney Discord server is the primary community for AI image generation with 20 million+ members. Browse others' generations for inspiration, get help with prompting, participate in office hours, and stay current with model updates. The most active AI community on Discord.
LangChain Community
Official Discord and GitHub Discussions community for LangChain — the leading framework for building LLM applications. Get help with integrations, share projects, discuss new features, and connect with the team. Active community of 100,000+ developers building with LLMs.
OpenAI Developer Forum
Official OpenAI community forum for developers building with the OpenAI API. Covers GPT-4o, Assistants API, fine-tuning, function calling, and ChatGPT integration questions. Monitored by OpenAI staff who respond to bugs and feature requests. Essential resource for OpenAI API developers.
Weights & Biases Community
Community hub for ML experiment tracking and MLOps practitioners using W&B. Includes forums, showcase gallery of W&B Reports, monthly community calls, and educational resources on ML experiment design, hyperparameter optimisation, and model evaluation.
Latent Space Discord
Community Discord for the Latent Space podcast — one of the most respected AI engineering podcasts. The Discord connects AI engineers, researchers, and builders discussing the latest AI developments, job opportunities, and technical deep-dives. High signal, practitioner-focused.
3Blue1Brown — Neural Networks
3Blue1Brown's visual mathematics YouTube channel includes a brilliant series on neural networks and deep learning. Uses animated visualisations to explain backpropagation, gradient descent, and transformers with unmatched intuitive clarity. Perfect first resource for understanding how AI works.
Chip Huyen — ML Systems Design
Chip Huyen's blog and book on machine learning systems design covers the full lifecycle of production ML: data engineering, feature stores, training, evaluation, deployment, and monitoring. The go-to resource for ML engineers moving from research to production.
Connected Papers
Visual tool for exploring academic literature. Enter a paper and Connected Papers generates a visual graph of related and citing papers, helping researchers discover the intellectual neighbourhood of any topic. Essential for literature reviews and understanding how a field has developed.
Open WebUI
Feature-rich, self-hosted web interface for running AI models locally or connecting to OpenAI-compatible APIs. Open WebUI provides a ChatGPT-like experience with multi-modal support, RAG integration, conversation history, model management, and user administration. Works with Ollama.
n8n — Workflow Automation
Open-source workflow automation platform with 400+ integrations and native AI capabilities. n8n lets you build complex automations visually, with AI nodes for LLM calls, embeddings, vector storage, and RAG pipelines. Self-hostable, source-available, and actively developed.
Flowise
Open-source drag-and-drop UI for building LangChain-based AI applications. Flowise lets you visually construct RAG pipelines, agent workflows, and chatbots without writing code. Deploy as a self-hosted API or embed in any application. 30,000+ GitHub stars.
AutoGen — Microsoft
Microsoft Research's framework for building multi-agent conversational AI systems. AutoGen enables multiple LLM agents to collaborate, critique each other's work, and iteratively solve complex tasks through structured conversations. Pioneered the conversation-driven multi-agent paradigm.
Eleuther AI Research
EleutherAI is a grassroots AI research collective focused on open-source AI and interpretability research. They produced GPT-Neo, GPT-J, GPT-NeoX, The Pile dataset, and Pythia. Their alignment and interpretability research (especially activation patching) is highly influential.
Semantic Scholar
AI-powered academic search engine from the Allen Institute for AI. Semantic Scholar indexes 200 million+ papers with AI-extracted insights: citation context, influential citations, abstract summaries, and related paper recommendations. Free API available for building research tools.
Pinecone Vector Database
Fully managed, serverless vector database built for production AI applications. Pinecone delivers millisecond-latency semantic search at billions-of-vector scale with metadata filtering, hybrid search (dense + sparse), and zero infrastructure management. The most widely adopted vector database.
LangSmith
Developer platform for debugging, testing, evaluating, and monitoring LLM applications. LangSmith provides full observability into LangChain runs, prompt versioning, dataset management for evaluations, and production monitoring. Essential for teams shipping reliable LLM products.
Weights & Biases
MLOps platform for experiment tracking, model evaluation, hyperparameter optimisation, and dataset versioning. W&B Weave adds LLM-specific observability: trace LLM calls, log prompts/responses, and build evaluation pipelines. Used by 1 million+ ML practitioners at leading AI labs.
Coursera Machine Learning Specialization
Andrew Ng's updated Machine Learning Specialization on Coursera — three courses covering supervised learning, unsupervised learning, and advanced ML. Uses Python, scikit-learn, and TensorFlow. The most popular ML course online with over 5 million enrolled learners.
Google Machine Learning Crash Course
Google's free, self-paced machine learning crash course with TensorFlow APIs. Covers ML fundamentals, gradient descent, neural networks, classification, and regularisation through interactive exercises and real-world case studies. No prior ML experience required.
Stanford CS231n — Convolutional Neural Networks
Stanford University's legendary computer vision course covering CNNs, image classification, object detection, segmentation, and generative models. Lecture videos, notes, and assignments are freely available. Taught by world-leading researchers including Fei-Fei Li.
Full Stack LLM Bootcamp
Comprehensive bootcamp covering the full stack of building LLM-powered applications: prompt engineering, embeddings, vector stores, RAG pipelines, fine-tuning, deployment, and evaluation. Taught by practitioners who have shipped production AI products at scale.
Replicate
Cloud platform for running and fine-tuning open-source AI models via a simple API. Run Llama 3, Stable Diffusion, Whisper, and thousands of community models with one API call and pay per second of compute. No GPU setup required — ideal for prototyping and production.
Modal
Cloud infrastructure platform purpose-built for AI and ML workloads. Modal lets you run Python functions on serverless GPUs with millisecond cold starts, scale to hundreds of GPUs instantly, and deploy model inference endpoints. Beloved by AI engineers for its clean developer experience.
Common Crawl
Petabyte-scale open web crawl dataset updated monthly containing raw web page data, extracted text, and metadata from billions of web pages. Used to pre-train GPT-3, Llama, and most large language models. Free to access via Amazon S3 on AWS Open Data.
LAION-5B Image-Text Dataset
LAION-5B is an open dataset of 5.85 billion image-text pairs scraped from the internet and used to train Stable Diffusion and CLIP models. Includes LAION-400M and LAION-Aesthetics subsets. Critical infrastructure for open-source image generation research.
Papers With Code — Datasets
Curated collection of machine learning benchmark datasets linked to the research papers that introduced them. Each dataset entry includes leaderboards showing which models achieve state-of-the-art results, with links to code and paper reproductions.
Open Images Dataset
Google's Open Images is a dataset of 9 million images annotated with image-level labels, object bounding boxes, object segmentation masks, and visual relationships. Covers 600 object classes and is widely used for computer vision model training and benchmarking.
The Pile — EleutherAI
The Pile is an 825GB diverse open-source language modelling dataset assembled by EleutherAI from 22 high-quality sub-datasets including Books3, OpenWebText2, GitHub, Wikipedia, arXiv, FreeLaw, and more. Used to train GPT-Neo, GPT-J, and other open-source LLMs.
Anthropic Research
Anthropic's research publications covering constitutional AI, interpretability, scaling laws, and AI safety. Anthropic publishes foundational work on making LLMs more honest, harmless, and helpful. The team behind Claude shares their most important findings openly.
Google DeepMind Research
Google DeepMind publishes research across reinforcement learning, protein folding (AlphaFold), game-playing AI (AlphaGo, Gemini), robotics, and scientific discovery. One of the most prolific and impactful AI research labs, responsible for some of the most cited papers in ML history.
OpenAI Cookbook
Official collection of example code, tutorials, and guides for working with the OpenAI API. Covers embeddings, fine-tuning, function calling, RAG, Assistants, batch processing, and production best practices. Maintained by OpenAI engineers with regular updates for new features.
TLDR AI
Part of the TLDR newsletter family, TLDR AI delivers a daily curated summary of the most important AI and ML news, research papers, and tool releases. Concise bullet-point format with links for deeper reading. One of the fastest-growing AI newsletters.
Import AI — Jack Clark
Weekly newsletter by Jack Clark (Anthropic co-founder) covering AI research with a focus on safety, policy, and technical depth. Import AI provides thoughtful analysis of frontier research papers and broader implications of AI development. Favourite of AI researchers.
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