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Your ML & Data Knowledge Wiki. Best practices and expert-level knowledge for Machine Learning and Data Engineering, covering 1000+ frameworks and libraries from training to deployment.
Browse implementation patterns, configuration guides, debugging heuristics, and battle-tested defaults for frameworks like vLLM, DeepSpeed, Megatron-LM, FlashAttention, Triton, Unsloth, LangChain, and many more. Every page is structured so both humans and AI agents can find what they need fast.
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| Category | Description | Browse |
|---|---|---|
| Workflows | Step-by-step processes and procedures | Browse All |
| Principles | Core ideas and foundational knowledge | Browse All |
| Implementations | Code-level details and modules | Browse All |
| Heuristics | Best practices and guidelines | Browse All |
| Environments | Setup and configuration guides | Browse All |
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Workflows
- Workflow:Langchain ai Langgraph Building a Stateful Graph
- Workflow:Microsoft Semantic kernel Plugin Integration And Function Calling
- Workflow:Vibrantlabsai Ragas Experiment Driven Development
- Workflow:BerriAI Litellm Proxy Server Deployment
- Workflow:AUTOMATIC1111 Stable diffusion webui Image postprocessing and upscaling
- Workflow:Isaac sim IsaacGymEnvs Factory Assembly Training
- Workflow:Mlc ai Web llm Basic Chat Completion
- Workflow:ArroyoSystems Arroyo Checkpoint Recovery
- Workflow:Facebookresearch Habitat lab PointNav PPO Training
- Workflow:PrefectHQ Prefect AI Data Analyst Agent
Principles
- Principle:Obss Sahi Prediction Merging
- Principle:Interpretml Interpret EBM JSON Serialization
- Principle:Vespa engine Vespa Tokenization
- Principle:Duckdb Duckdb String Similarity
- Principle:FlowiseAI Flowise Node Registry Loading
- Principle:Volcengine Verl Evaluation And Checkpointing
- Principle:Run llama Llama index Finetuned Model Retrieval
- Principle:Anthropics Anthropic sdk python Tool Result Submission
- Principle:Microsoft BIPIA Distributed Finetuning
- Principle:Speechbrain Speechbrain Permutation Invariant Training
Implementations
- Implementation:InternLM Lmdeploy Core Smem
- Implementation:Openai Openai node Node ESM Lockfile
- Implementation:Datahub project Datahub MetadataResponseFuture
- Implementation:Norrrrrrr lyn WAInjectBench SentenceTransformer Init
- Implementation:Lance format Lance TakeBench
- Implementation:Deepspeedai DeepSpeed Init Inference
- Implementation:Dagster io Dagster Helm Test Fixtures
- Implementation:Huggingface Datasets Xml Builder
- Implementation:Deepspeedai DeepSpeed PipelineEngine Train Batch
- Implementation:Online ml River Cluster TextClust
Heuristics
- Heuristic:Alibaba MNN NC4HW4 Data Layout
- Heuristic:Microsoft Onnxruntime Flash Attention Optimization
- Heuristic:Sgl project Sglang Schedule Conservativeness Tuning
- Heuristic:ContextualAI HALOs Online Round Budgeting
- Heuristic:Bigscience workshop Petals Randomized Rebalancing Intervals
- Heuristic:Alibaba ROLL Dynamic Batching Token Limits
- Heuristic:Groq Groq python Retry Backoff Strategy
- Heuristic:Alibaba ROLL PPO Clipping Defaults
- Heuristic:Apache Beam Lock Contention Batching
- Heuristic:Deepspeedai DeepSpeed Sequence Parallel PyTorch Version
Environments
- Environment:Gretelai Gretel synthetics TensorFlow GPU Environment
- Environment:MarketSquare Robotframework browser CI GitHub Actions
- Environment:Allenai Open instruct Python 3 12 Runtime
- Environment:OWASP Www project top 10 for large language model applications GenAI Red Team Environment
- Environment:Treeverse LakeFS Web UI Environment
- Environment:Langgenius Dify Redis And Celery Environment
- Environment:Axolotl ai cloud Axolotl Multi GPU
- Environment:Shiyu coder Kronos PyTorch CUDA Environment
- Environment:Openai Openai agents python LiteLLM Dependencies
- Environment:Huggingface Alignment handbook BitsAndBytes CUDA