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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:Vibrantlabsai Ragas Agent Evaluation
- Workflow:Dagster io Dagster ML Pipeline
- Workflow:Haifengl Smile Data Loading Pipeline
- Workflow:Microsoft Onnxruntime Python Inference Pipeline
- Workflow:Scikit learn contrib Imbalanced learn Imbalanced Model Evaluation
- Workflow:DataExpert io Data engineer handbook Flink Kafka Streaming Pipeline
- Workflow:Iamhankai Forest of Thought Game24 Forest Solving
- Workflow:Turboderp org Exllamav2 Interactive Chat
- Workflow:PeterL1n BackgroundMattingV2 Video matting inference
- Workflow:Trailofbits Fickling PyTorch Payload Injection
Principles
- Principle:Langgenius Dify Deployment and API Access
- Principle:Mit han lab Llm awq AWQ HuggingFace Export
- Principle:Langgenius Dify React Context Pattern
- Principle:Iterative Dvc Plot Definition Collection
- Principle:Neuml Txtai Workflow Execution
- Principle:Datahub project Datahub Proto2DataHub Configuration
- Principle:Tensorflow Serving Source Routing
- Principle:Triton inference server Server Container Verification
- Principle:Microsoft Agent framework Sequential Orchestration
- Principle:Vllm project Vllm Draft Model Acquisition
Implementations
- Implementation:Openai Openai node Completions Create
- Implementation:Online ml River Drift ADWIN
- Implementation:Deepspeedai DeepSpeed CPU Lion Impl
- Implementation:Pytorch Serve Diffusion Fast Handler
- Implementation:Avhz RustQuant Graph and Variable
- Implementation:Treeverse LakeFS Java SDK Model ObjectStats
- Implementation:Hpcaitech ColossalAI GRPOConsumer
- Implementation:Mlc ai Mlc llm Download and cache mlc weights
- Implementation:Apache Flink CongestionControlRateLimitingStrategy Builder
- Implementation:Microsoft Semantic kernel VectorStoreTextSearch RAG
Heuristics
- Heuristic:Neuml Txtai Memory Streaming Optimization
- Heuristic:DataExpert io Data engineer handbook Watermark Late Arrival Tolerance
- Heuristic:Cohere ai Cohere python ToolCallV2 Auto UUID Override
- Heuristic:EvolvingLMMs Lab Lmms eval Limit Flag Testing Only
- Heuristic:Gretelai Gretel synthetics Parallel Generation CUDA Disable
- Heuristic:Microsoft LoRA Label Smoothing NLG
- Heuristic:Norrrrrrr lyn WAInjectBench Union Ensemble Maximize Recall
- Heuristic:Ggml org Llama cpp Thread Count Tuning
- Heuristic:MarketSquare Robotframework browser Shared Node Process For Parallel
- Heuristic:SeldonIO Seldon core Over Commit Memory Tip
Environments
- Environment:Mistralai Client python Python SDK Environment
- Environment:ArroyoSystems Arroyo Kubernetes Deployment
- Environment:FlowiseAI Flowise Queue Mode Environment
- Environment:Rapidsai Cuml Python RAPIDS Stack
- Environment:Evidentlyai Evidently Grafana Monitoring Environment
- Environment:Speechbrain Speechbrain PyTorch CUDA Runtime
- Environment:Apache Dolphinscheduler ZooKeeper Registry
- Environment:Facebookresearch Habitat lab CUDA GPU Training Environment
- Environment:Kubeflow Kubeflow Kubectl Kustomize CLI Environment
- Environment:Microsoft Playwright Node Runtime Environment