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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:Cleanlab Cleanlab Token Classification Label Quality
- Workflow:Neuml Txtai Pipeline Workflow Chaining
- Workflow:Openai Whisper Word Level Timestamps
- Workflow:OpenGVLab InternVL Preference Optimization
- Workflow:Spcl Graph of thoughts GoT Document Merging Pipeline
- Workflow:DataTalksClub Data engineering zoomcamp dbt Analytics Transformation
- Workflow:Googleapis Python genai Context Caching
- Workflow:Facebookresearch Audiocraft EnCodec Compression Training
- Workflow:OpenRLHF OpenRLHF PPO Ray Training
- Workflow:Vespa engine Vespa CI CD build pipeline
Principles
- Principle:Lm sys FastChat Model Worker Inference
- Principle:Kubeflow Pipelines Model Evaluation Metrics
- Principle:Facebookresearch Audiocraft Token Sampling Strategies
- Principle:Vespa engine Vespa Unicode Normalization
- Principle:Sgl project Sglang Model Quantization Configuration
- Principle:Apache Airflow Helm Values Configuration
- Principle:Google deepmind Dm control Terrain Arena Building
- Principle:PacktPublishing LLM Engineers Handbook SageMaker Evaluation Orchestration
- Principle:Marker Inc Korea AutoRAG Export And Corpus Remapping
- Principle:Huggingface Datasets Dataset Metadata Inspection
Implementations
- Implementation:FMInference FlexLLMGen DeepSpeed Reduction Utils
- Implementation:FlagOpen FlagEmbedding LLM Embedder SRLM
- Implementation:OpenHands OpenHands LinearView
- Implementation:SeldonIO Seldon core Seldon Model CRD Explainer Deploy
- Implementation:Volcengine Verl Multimodal Rollout Request
- Implementation:Confident ai Deepeval KeyFileHandler
- Implementation:NVIDIA TransformerEngine DelayedScaling Recipe
- Implementation:TobikoData Sqlmesh Documentation Component
- Implementation:Groq Groq python ErrorObject Type
- Implementation:Mage ai Mage ai Front Client
Heuristics
- Heuristic:Spcl Graph of thoughts Backoff Retry On API Errors
- Heuristic:Apache Beam GC Thrashing Detection
- Heuristic:Avhz RustQuant Learning Rate Tuning
- Heuristic:Ucbepic Docetl Validation Retry Strategy
- Heuristic:Mlc ai Web llm Tokenizer JSON Preference
- Heuristic:Astronomer Astronomer cosmos Cache Strategy Optimization
- Heuristic:Tencent Ncnn Optimize Before Quantize
- Heuristic:Farama Foundation Gymnasium Action Space Normalization Tip
- Heuristic:Mlflow Mlflow Batch Logging Size Limits
- Heuristic:Norrrrrrr lyn WAInjectBench NaN Inf Fallback FP32 Recovery
Environments
- Environment:Shiyu coder Kronos HuggingFace Hub Access
- Environment:Turboderp org Exllamav2 Flash Attention Backend
- Environment:Alibaba ROLL CUDA GPU Environment
- Environment:Huggingface Datasets Lance Dependencies
- Environment:Openai Openai python Azure OpenAI
- Environment:Openai Openai node Node 20 Runtime
- Environment:Evidentlyai Evidently Spark Engine Environment
- Environment:Openai CLIP PyTorch CUDA Runtime
- Environment:Datahub project Datahub Java Build
- Environment:Openai Openai agents python Voice Dependencies