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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:Eric mitchell Direct preference optimization SFT Training
- Workflow:Datajuicer Data juicer Text Data Processing Pipeline
- Workflow:Treeverse LakeFS S3 Gateway Integration
- Workflow:Microsoft Playwright End to end test authoring
- Workflow:Nightwatchjs Nightwatch E2E Test Authoring
- Workflow:ArroyoSystems Arroyo Local Pipeline Execution
- Workflow:LaurentMazare Tch rs MNIST Training
- Workflow:Google deepmind Mujoco Offscreen video recording
- Workflow:Anthropics Anthropic sdk python Basic Message Conversation
- Workflow:Tensorflow Tfjs Sequential Model Training
Principles
- Principle:OpenHands OpenHands Agent Summary Callback
- Principle:Lucidrains X transformers Non Autoregressive Wrapper Setup
- Principle:Apache Beam Element Bundling
- Principle:Ollama Ollama Token Sampling
- Principle:Tensorflow Tfjs Data Preprocessing Layers
- Principle:Triton inference server Server QA Test Model Generation
- Principle:Mlflow Mlflow Prompt Registration
- Principle:Mlc ai Web llm Tool Definition
- Principle:Duckdb Duckdb Benchmark Build Configuration
- Principle:Avhz RustQuant Analytic Option Pricing Engine
Implementations
- Implementation:Bitsandbytes foundation Bitsandbytes Quantize Blockwise
- Implementation:Apache Paimon DlfProvider
- Implementation:Scikit learn Scikit learn Get Feature Names
- Implementation:Guardrails ai Guardrails Refrain Action
- Implementation:Mage ai Mage ai Stripe Payment Intents Schema
- Implementation:Recommenders team Recommenders LightFM Utils
- Implementation:Neuml Txtai ServiceTask
- Implementation:Tencent Ncnn Draw Rectangle And Text
- Implementation:Farama Foundation Gymnasium FuncEnv
- Implementation:TobikoData Sqlmesh UseLocalStorage
Heuristics
- Heuristic:Cleanlab Cleanlab Multiprocessing Platform Strategy
- Heuristic:Apache Dolphinscheduler Failover Marker TTL
- Heuristic:Apache Druid Auto Granularity Selection
- Heuristic:Turboderp org Exllamav2 Dynamic Generator Tuning
- Heuristic:Lm sys FastChat Flash Attention GPU Requirements
- Heuristic:Facebookresearch Audiocraft Gradient Balancing For Multi Loss
- Heuristic:Shiyu coder Kronos Learning Rate And Optimizer Tuning
- Heuristic:Teamcapybara Capybara Negative Predicate Matching
- Heuristic:Tencent Ncnn Optimize Before Quantize
- Heuristic:Lance format Lance Fragment Sizing Strategy
Environments
- Environment:Gretelai Gretel synthetics PyTorch CUDA Environment
- Environment:PeterL1n BackgroundMattingV2 PyTorch CUDA
- Environment:SqueezeAILab ETS Evaluation Python Stack
- Environment:Online ml River Python Runtime Environment
- Environment:DataExpert io Data engineer handbook Spark Iceberg Docker Environment
- Environment:Microsoft Semantic kernel OpenAI API Environment
- Environment:Onnx Onnx Cpp Build Environment
- Environment:Haotian liu LLaVA Python CUDA Training Environment
- Environment:Obss Sahi Python Image Processing
- Environment:Haifengl Smile Native BLAS LAPACK ARPACK