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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:Apache Spark Building and Testing
- Workflow:Googleapis Python genai Model Fine Tuning
- Workflow:Apache Airflow Kubernetes Deployment via Helm
- Workflow:Langfuse Langfuse Dataset experiment pipeline
- Workflow:Predibase Lorax Multi Adapter Merging
- Workflow:ChenghaoMou Text dedup Benchmark Evaluation
- Workflow:Microsoft Semantic kernel Process Orchestration
- Workflow:Microsoft Semantic kernel Agent Conversation And Orchestration
- Workflow:Apache Dolphinscheduler Workflow Execution Lifecycle
- Workflow:Speechbrain Speechbrain Whisper ASR Finetuning
Principles
- Principle:Apache Dolphinscheduler RPC Service Contract Definition
- Principle:LaurentMazare Tch rs Feature Extraction
- Principle:Arize ai Phoenix Span Annotation
- Principle:Ray project Ray Actor Method Invocation
- Principle:OpenRLHF OpenRLHF Rule Based Reward Functions
- Principle:Microsoft Semantic kernel RAG Chat Augmentation
- Principle:Kserve Kserve Multi Model Shared Service
- Principle:Mlflow Mlflow Protobuf Code Generation
- Principle:SeleniumHQ Selenium Browser Interaction
- Principle:Datahub project Datahub Client Resource Cleanup
Implementations
- Implementation:Openai Openai python Batch Usage Model
- Implementation:Langgenius Dify Next Config
- Implementation:Apache Airflow OtelTrace
- Implementation:Spotify Luigi FTPTarget
- Implementation:NVIDIA TransformerEngine TE DotProductAttention
- Implementation:Avhz RustQuant BarrierOption
- Implementation:OpenHands OpenHands JiraIntegrationStore
- Implementation:Mlc ai Mlc llm Fuse Transpose Matmul
- Implementation:Kserve Kserve DeepSeek R1 PD DeepEP HT Sample
- Implementation:Speechbrain Speechbrain Prepare Voicebank Revb
Heuristics
- Heuristic:Microsoft Autogen Warning Deprecated JSON Env Files
- Heuristic:Treeverse LakeFS Action Cache Wait Tip
- Heuristic:HKUDS AI Trader Sortino Ratio Capping
- Heuristic:PeterL1n BackgroundMattingV2 Mixed Precision Training
- Heuristic:Lm sys FastChat Tokenizer Offset Correction
- Heuristic:Mit han lab Llm awq Skip QK Projection Clipping
- Heuristic:Neuml Txtai Llama Cpp Context Fallback
- Heuristic:Interpretml Interpret EBM Hyperparameter Tuning Guide
- Heuristic:Pytorch Serve LLM Timeout Configuration
- Heuristic:Princeton nlp SimPO Dropout Disabling
Environments
- Environment:Vllm project Vllm Buildkite
- Environment:Datahub project Datahub Python Ingestion
- Environment:Kubeflow Kubeflow Istio Certmanager Dex Environment
- Environment:Sktime Pytorch forecasting Optuna Tuning Dependencies
- Environment:Huggingface Diffusers Quantization Environment
- Environment:NVIDIA TransformerEngine GPU Compute Capability
- Environment:Tensorflow Serving Python Client Environment
- Environment:Zai org CogVideo Diffusers Inference Environment
- Environment:Haifengl Smile Native BLAS LAPACK ARPACK
- Environment:VainF Torch Pruning YOLO Pruning Dependencies