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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:Huggingface Trl Direct Preference Optimization
- Workflow:Alibaba MNN Python Model Inference
- Workflow:SeleniumHQ Selenium Browser Session Setup
- Workflow:Apache Kafka Coordinator Runtime Lifecycle
- Workflow:OWASP Www project top 10 for large language model applications Agentic Security Assessment
- Workflow:Unstructured IO Unstructured Connector Ingest Pipeline
- Workflow:Groq Groq python Streaming Chat Completion
- Workflow:LLMBook zh LLMBook zh github io Data Preprocessing Pipeline
- Workflow:Apache Beam Twister2 Batch Execution
- Workflow:Trailofbits Fickling PyTorch Format Identification
Principles
- Principle:AUTOMATIC1111 Stable diffusion webui Prompt Syntax
- Principle:Treeverse LakeFS API Authentication Specification
- Principle:Apache Flink Hybrid Source Initialization
- Principle:ClickHouse ClickHouse Core Compiler Macros
- Principle:ClickHouse ClickHouse SSL TLS Configuration
- Principle:Bentoml BentoML Model Loading From Store
- Principle:Huggingface Diffusers Training Environment Setup
- Principle:Lance format Lance Compaction Commit
- Principle:Lm sys FastChat Chat Data Cleaning
- Principle:Facebookresearch Audiocraft Conditioning Preparation
Implementations
- Implementation:Vibrantlabsai Ragas BasePrompt
- Implementation:Bitsandbytes foundation Bitsandbytes Backend Quantization Tables
- Implementation:Infiniflow Ragflow DatasetSidebar Component
- Implementation:Dagster io Dagster Asset Check Decorator
- Implementation:Deepset ai Haystack PyPDFToDocument
- Implementation:Evidentlyai Evidently Legacy IsValidSQL Feature
- Implementation:Apache Shardingsphere StatisticsRefreshEngine Refresh
- Implementation:Microsoft Onnxruntime TrainingDataLoader
- Implementation:Ucbepic Docetl ChatRoute
- Implementation:Explodinggradients Ragas Dataset Constructor
Heuristics
- Heuristic:ThreeSR Awesome Inference Time Scaling Empty Venue Default Tip
- Heuristic:Apache Kafka JVM GC Tuning Defaults
- Heuristic:Google research Deduplicate text datasets Variable Width Pointer Optimization
- Heuristic:Sgl project Sglang Schedule Conservativeness Tuning
- Heuristic:Spcl Graph of thoughts Backoff Retry On API Errors
- Heuristic:EvolvingLMMs Lab Lmms eval Distributed Padding Strategy
- Heuristic:Arize ai Phoenix Warning Deprecated VertexAIModel
- Heuristic:Protectai Modelscan Unknown Opcodes Assume Critical
- Heuristic:OpenGVLab InternVL Pixel Shuffle Downsampling
- Heuristic:LaurentMazare Tch rs Hidden Dimension Alignment
Environments
- Environment:Huggingface Peft BitsAndBytes Quantization
- Environment:ArroyoSystems Arroyo Kubernetes Deployment
- Environment:Kserve Kserve Knative Serving
- Environment:Langgenius Dify Node Frontend Environment
- Environment:Lm sys FastChat LoRA QLoRA Training Environment
- Environment:Openai Evals Python Runtime
- Environment:Mlc ai Web llm WebGPU Browser Runtime
- Environment:Alibaba ROLL Python Runtime Environment
- Environment:Isaac sim IsaacGymEnvs Pip Dependencies
- Environment:Confident ai Deepeval Python 3 9 Runtime