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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:Microsoft Playwright Codegen test recording
- Workflow:Openclaw Openclaw Gateway Operations And Diagnostics
- Workflow:Princeton nlp Tree of thought llm Baseline comparison
- Workflow:Truera Trulens Custom App Instrumentation And Evaluation
- Workflow:Google research Deduplicate text datasets Wiki40B TFDS deduplication
- Workflow:Bigscience workshop Petals Prompt Tuning Chatbot
- Workflow:Interpretml Interpret EBM Training And Prediction
- Workflow:MarketSquare Robotframework browser API Testing via Browser
- Workflow:Deepspeedai DeepSpeed Inference Engine Optimization
- Workflow:Dotnet Machinelearning ONNX Model Scoring
Principles
- Principle:Datahub project Datahub Spark Event Interception
- Principle:LLMBook zh LLMBook zh github io Low Rank Adaptation
- Principle:Huggingface Trl PPO Training Loop
- Principle:Langchain ai Langgraph Task Definition
- Principle:VainF Torch Pruning Latency Benchmarking
- Principle:Lance format Lance Fragment Rewriting
- Principle:NVIDIA DALI PyTorch Data Output
- Principle:MarketSquare Robotframework browser Installation Path Selection
- Principle:Microsoft Autogen Hierarchical Agent Composition
- Principle:Neuml Txtai Text Tokenization
Implementations
- Implementation:Apache Druid ExecutionDetailsPane
- Implementation:Google deepmind Dm control MJCF Find Modify
- Implementation:Hpcaitech ColossalAI GRPOConsumer
- Implementation:Alibaba MNN RapidJSON Reader
- Implementation:Huggingface Transformers Fetch Hub Objects For CI
- Implementation:Explodinggradients Ragas BaseBackend Class
- Implementation:Infiniflow Ragflow FeedbackDialog Component
- Implementation:Alibaba MNN OpenCL CL2 HPP Header
- Implementation:Google deepmind Mujoco Engine Collision SDF
- Implementation:Vllm project Vllm SGL MoE
Heuristics
- Heuristic:FMInference FlexLLMGen OOM Memory Management
- Heuristic:Guardrails ai Guardrails Guard History Memory Management
- Heuristic:Arize ai Phoenix AIMD Concurrency Control
- Heuristic:Shiyu coder Kronos Learning Rate And Optimizer Tuning
- Heuristic:Pytorch Serve CPU Performance Tuning
- Heuristic:FlowiseAI Flowise Document Loader Bypass Optimization
- Heuristic:Lance format Lance BM25 FTS Configuration
- Heuristic:InternLM Lmdeploy OOM Troubleshooting
- Heuristic:CrewAIInc CrewAI LLM Provider Message Workarounds
- Heuristic:AnswerDotAI RAGatouille Searcher Configuration By Collection Size
Environments
- Environment:Openai Openai python Python 3 9 Plus
- Environment:Dotnet Machinelearning ONNX Runtime Environment
- Environment:Alibaba ROLL DeepSpeed Training Environment
- Environment:FlagOpen FlagEmbedding Finetuning Environment
- Environment:Alibaba MNN Python Export Environment
- Environment:Ggml org Ggml CUDA GPU Environment
- Environment:CrewAIInc CrewAI LLM Provider Credentials
- Environment:Eventual Inc Daft Ray Distributed Runner
- Environment:Datahub project Datahub Spark Lineage Environment
- Environment:Google deepmind Dm control Python MuJoCo Runtime