AI
Artificial intelligence: machine learning, neural networks, large language models, deep learning, AI research, and AI tools.
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Microsoft Agent Framework learn.microsoft.com
Microsoft's successor to AutoGen and Semantic Kernel for agents and graph-based workflows.
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DeepLearning.AI Short Courses learn.deeplearning.ai
Focused courses on current generative AI engineering techniques.
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Langfuse langfuse.com
Tracing, evaluation, prompt management, and metrics for LLM applications.
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MIT 6.S191: Introduction to Deep Learning introtodeeplearning.com
Deep learning foundations and applications.
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Hugging Face LLM Course huggingface.co
Transformers, fine-tuning, datasets, and modern NLP tooling.
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Google Agent Development Kit google.github.io
Google's framework for developing and evaluating agents.
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OWASP Top 10 for LLM Applications genai.owasp.org
Risks and mitigations for developing and deploying generative AI applications.
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Full Stack Deep Learning fullstackdeeplearning.com
The full lifecycle of building and shipping AI products.
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vLLM docs.vllm.ai
An inference and serving engine for language models.
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Ragas docs.ragas.io
Evaluation and experimentation for retrieval and generative AI applications.
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LlamaIndex docs.llamaindex.ai
Data ingestion, indexing, retrieval, and agent workflows.
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LiteLLM docs.litellm.ai
A model gateway and unified interface for multiple model providers.
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Haystack docs.haystack.deepset.ai
Modular pipelines for retrieval and generative AI applications.
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Anthropic Prompt Engineering docs.anthropic.com
Techniques for defining success criteria, testing prompts, and improving model behaviour.
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Stanford CS336: Language Modeling from Scratch cs336.stanford.edu
Build language models from data preparation through evaluation and deployment.
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OpenAI Cookbook cookbook.openai.com
Code examples for structured outputs, tool use, retrieval, evals, and other LLM application patterns.
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Google Generative AI Learning Path cloudskillsboost.google
An introductory path through generative AI concepts and Google Cloud tooling.
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A Practical Guide to Building Agents cdn.openai.com
OpenAI's guide to models, tools, instructions, orchestration, and guardrails.
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Constitutional AI arxiv.org
A method for training helpful and harmless AI assistants using written principles.
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ReAct arxiv.org
Combined reasoning traces with actions for tool-using language-model agents.
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Training Compute-Optimal Large Language Models arxiv.org
Showed how model size and training data should scale together under a compute budget.
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Training Language Models to Follow Instructions with Human Feedback arxiv.org
Established the instruction tuning and RLHF recipe used by InstructGPT.
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LoRA arxiv.org
Introduced low-rank adaptation for parameter-efficient model fine-tuning.
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Language Models are Few-Shot Learners arxiv.org
Demonstrated in-context learning at scale.
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Retrieval-Augmented Generation arxiv.org
Combined parametric language models with external retrieval for knowledge-intensive tasks.
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Scaling Laws for Neural Language Models arxiv.org
Explored relationships between model performance, data, and compute.
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How We Built Our Multi-Agent Research System anthropic.com
Production lessons on orchestrator-worker agents, parallel search, evaluation, and operational reliability.
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Demystifying Evals for AI Agents anthropic.com
A practical method for building task suites, graders, transcripts, and evaluation harnesses.
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Artificial Intelligence: A Modern Approach aima.cs.berkeley.edu
The broad reference for classical AI, including search, reasoning, planning, learning, and robotics.
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AI Engineer aiengineer.co
A paid program for agentic coding and building, testing, and shipping production AI systems.
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Pydantic AI ai.pydantic.dev
Typed agent development built around Pydantic.
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MIT's Artificial Intelligence Lab Publications dspace.mit.edu
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Sibyl users.soe.ucsc.edu
System for Large Scale Machine Learning at Google.
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Azure ML Studio studio.azureml.net
Cloud-based AzureML, R, Python Machine Learning platform
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IEEE Transactions on Network Science and Engineering ieeexplore.ieee.org
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Fundamentals of Brain Network Analysis elsevier.com
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Applied Network Science appliednetsci.springeropen.com
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Spark MLlib spark.apache.org
a Spark implementation of some common machine learning (ML) functionality.
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PredictionIO predictionio.incubator.apache.org
machine learning server built on Hadoop, Mahout and Cascading.
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MOA moa.cms.waikato.ac.nz
MOA performs big data stream mining in real time, and large scale machine learning.
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MLbase mlbase.org
distributed machine learning libraries for the BDAS stack.
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Graph-Powered Machine Learning manning.com
Alessandro Negro. Combine graph theory and models to improve machine learning projects
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ENCOG heatonresearch.com
machine learning framework that supports a variety of advanced algorithms, as well as support classes to normalize and process data.
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Torch github.com
A deep learning library with a Lua API, supported by NYU and Facebook.
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Theano github.com
A Python-focused machine learning library supported by the University of Montreal.
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Deeplearning4j github.com
Fast, open deep learning for the JVM (Java, Scala, Clojure). A neural network configuration layer powered by a C++ library. Uses Spark and Hadoop to train nets on multiple GPUs and CPUs.
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etcML etcml.com
text classification with machine learning.
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LinkedIn Galene engineering.linkedin.com
search architecture at LinkedIn.
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Apache SystemML systemml.apache.org
Declarative machine learning framework on top of Spark.
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