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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:AnswerDotAI RAGatouille ColBERT Training
- Workflow:Predibase Lorax Single LoRA Inference
- Workflow:Onnx Onnx Model Composition
- Workflow:Googleapis Python genai Multimodal Content Generation
- Workflow:Huggingface Diffusers LoRA Finetuning
- Workflow:Google deepmind Dm control Locomotion Task Setup
- Workflow:Mlc ai Mlc llm Model Compilation
- Workflow:NVIDIA NeMo Curator Text Curation Pipeline
- Workflow:Kornia Kornia Image Feature Matching
- Workflow:Microsoft Playwright AI agent driven testing
Principles
- Principle:SeleniumHQ Selenium Driver Service Lifecycle
- Principle:Tensorflow Serving gRPC Service Stubs
- Principle:LLMBook zh LLMBook zh github io Instruction Data Formatting
- Principle:Langgenius Dify Vector Database Selection
- Principle:Risingwavelabs Risingwave Iceberg Table Maintenance
- Principle:DataTalksClub Data engineering zoomcamp Streaming Data Model
- Principle:Bigscience workshop Petals Distributed Autograd
- Principle:Microsoft DeepSpeedExamples Multimodal Distributed Training
- Principle:Apache Hudi Clustering Strategy Configuration
- Principle:Ucbepic Docetl Pipeline Execution
Implementations
- Implementation:EvolvingLMMs Lab Lmms eval Uni MMMU Visual Puzzle Utils
- Implementation:Deepspeedai DeepSpeed Initialize For SFT
- Implementation:Apache Flink CompactorOperator ProcessElement
- Implementation:Trailofbits Fickling Interpreter To Ast
- Implementation:Haosulab ManiSkill BoundingCylinder
- Implementation:Infiniflow Ragflow Config Utils
- Implementation:PeterL1n BackgroundMattingV2 DATA PATH config
- Implementation:Astronomer Astronomer cosmos DbtVirtualenvBaseOperator
- Implementation:Kserve Kserve Controller Manager Deployment
- Implementation:Sgl project Sglang Generation Output Dict
Heuristics
- Heuristic:Google deepmind Dm control Prop Settling Physics Tuning
- Heuristic:Puppeteer Puppeteer Chrome Default Launch Arguments
- Heuristic:Predibase Lorax Warning Deprecated BitsAndBytes 8bit
- Heuristic:ThreeSR Awesome Inference Time Scaling API Rate Limiting Tip
- Heuristic:Huggingface Datasets Batch Size Optimization
- Heuristic:LMCache LMCache CacheGen Quantization Strategy
- Heuristic:Datahub project Datahub Validation Across All APIs
- Heuristic:Zai org CogVideo LoRA Configuration Tips
- Heuristic:Online ml River HST Feature Scaling Requirement
- Heuristic:AnswerDotAI RAGatouille FAISS Vs PyTorch KMeans Indexing
Environments
- Environment:Testtimescaling Testtimescaling github io GitHub Actions Runner
- Environment:Mbzuai oryx Awesome LLM Post training Python Requests
- Environment:Marker Inc Korea AutoRAG Vector Database Backends
- Environment:Apache Druid Web Console Development
- Environment:SeldonIO Seldon core Python ML Dependencies Environment
- Environment:Farama Foundation Gymnasium Box2D Physics Backend
- Environment:Facebookresearch Habitat lab SLURM Distributed Environment
- Environment:Langgenius Dify Python Backend Environment
- Environment:Interpretml Interpret Visualization Environment
- Environment:Kserve Kserve Cert Manager