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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:Togethercomputer Together python Chat Completion
- Workflow:BerriAI Litellm Response Caching
- Workflow:Apache Shardingsphere Metadata DDL Refresh
- Workflow:Onnx Onnx External Data Handling
- Workflow:Microsoft Autogen Studio Team Deployment
- Workflow:SeleniumHQ Selenium Selenium Grid Deployment
- Workflow:Guardrails ai Guardrails Server Deployment
- Workflow:Alibaba MNN Model Conversion Pipeline
- Workflow:Apache Shardingsphere Shadow Rule Configuration
- Workflow:LMCache LMCache P2P KV Cache Sharing
Principles
- Principle:Testtimescaling Testtimescaling github io Integration Verification
- Principle:Apache Paimon Type System
- Principle:Nightwatchjs Nightwatch Project Initialization
- Principle:Isaac sim IsaacGymEnvs Task Registration
- Principle:Zai org CogVideo 3D Video Encoding
- Principle:ContextualAI HALOs Policy Sampling
- Principle:Ggml org Llama cpp ComputeGraph
- Principle:Mlc ai Mlc llm Native Application Building
- Principle:Sktime Pytorch forecasting V2 Model Base
- Principle:Kubeflow Pipelines Task Resource Configuration
Implementations
- Implementation:Openai Openai python Chat Completion Response
- Implementation:Scikit learn contrib Imbalanced learn BalancedRandomForestClassifier
- Implementation:Triton inference server Server JetsonCommonHeader
- Implementation:Hpcaitech ColossalAI DatasetEvaluator
- Implementation:Haifengl Smile PerfectHash
- Implementation:Langchain ai Langgraph StateGraph Add Edge
- Implementation:Onnx Onnx Cpp2py Export
- Implementation:Triton inference server Server L0 Response Cache Test
- Implementation:Open compass VLMEvalKit WeThinkVL
- Implementation:Microsoft Autogen Studio Type Guards
Heuristics
- Heuristic:Rapidsai Cuml GPU Cache Alignment
- Heuristic:Sktime Pytorch forecasting Encoder Decoder Length Limits
- Heuristic:Langchain ai Langgraph Stream Mode Selection
- Heuristic:MaterializeInc Materialize Docker Image Cache Lookup
- Heuristic:Princeton nlp SimPO Left Truncation Strategy
- Heuristic:Apache Airflow Variable Access Pattern
- Heuristic:Trailofbits Fickling Allowlist Maintenance
- Heuristic:Haotian liu LLaVA Flash Attention GPU Requirement
- Heuristic:SeleniumHQ Selenium Thread Safety With ThreadGuard
- Heuristic:Elevenlabs Elevenlabs python TTS Model Selection
Environments
- Environment:Gretelai Gretel synthetics PyTorch CUDA Environment
- Environment:Snorkel team Snorkel PySpark
- Environment:Apache Kafka Docker Build Environment
- Environment:Recommenders team Recommenders GPU CUDA Environment
- Environment:Spotify Luigi AWS S3 Storage
- Environment:Mbzuai oryx Awesome LLM Post training Python Requests
- Environment:Mistralai Client python Agents Environment
- Environment:Kornia Kornia PyTorch Python Environment
- Environment:Google research Deduplicate text datasets Python TFDS Environment
- Environment:Evidentlyai Evidently SQL Storage Environment