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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:OpenBMB UltraFeedback Dataset Construction
- Workflow:Sgl project Sglang Structured Output Generation
- Workflow:ChenghaoMou Text dedup Suffix Array Deduplication
- Workflow:Huggingface Optimum GPTQ Quantization
- Workflow:Kubeflow Pipelines Iterative Model Training
- Workflow:Cohere ai Cohere python Tool Use Agentic Chat
- Workflow:Trailofbits Fickling Safe ML Model Loading
- Workflow:Huggingface Transformers 3D Parallel Distributed Training
- Workflow:Promptfoo Promptfoo Project Initialization
- Workflow:Apache Flink File Source Pipeline
Principles
- Principle:Fastai Fastbook Model Ensembling
- Principle:Huggingface Datasets Dataset Mapping
- Principle:FMInference FlexLLMGen Learning Rate Scheduling
- Principle:Turboderp org Exllamav2 Device Management
- Principle:Romsto Speculative Decoding Logits Processing
- Principle:Interpretml Interpret Local Explanation Generation
- Principle:Explodinggradients Ragas LLM Provider Abstraction
- Principle:TA Lib Ta lib python Stream Event Integration
- Principle:Alibaba ROLL LoRA Parameter Optimization
- Principle:ClickHouse ClickHouse Program Component Compilation
Implementations
- Implementation:Webdriverio Webdriverio WebDriver Types
- Implementation:Evidentlyai Evidently Legacy OpenAI Feature
- Implementation:SeleniumHQ Selenium FirefoxCommandContext
- Implementation:Puppeteer Puppeteer EventEmitter
- Implementation:Google deepmind Mujoco Engine Island
- Implementation:NVIDIA NeMo Curator VLLMEmbedder
- Implementation:Kserve Kserve InferenceService CRD Spec
- Implementation:Bentoml BentoML Service Loader
- Implementation:Langchain ai Langgraph Pregel Invoke For Functional
- Implementation:Langfuse Langfuse Tracing Factory
Heuristics
- Heuristic:Apache Druid Auto Granularity Selection
- Heuristic:Sktime Pytorch forecasting Encoder Decoder Length Limits
- Heuristic:Sgl project Sglang Memory Fraction Tuning
- Heuristic:Alibaba MNN LLM Runtime Tuning
- Heuristic:Apache Shardingsphere DDL Refresher Superclass Fallback
- Heuristic:Neuml Txtai LLM Context Window Fallback
- Heuristic:NVIDIA DALI Last Batch Policy Selection
- Heuristic:Deepseek ai Janus Image Generation Prompt Tips
- Heuristic:TA Lib Ta lib python Unstable Period Configuration
- Heuristic:Infiniflow Ragflow Reranking Weight Tuning
Environments
- Environment:Arize ai Phoenix LLM Provider SDKs
- Environment:CARLA simulator Carla Simulation Runtime
- Environment:Sdv dev SDV GPU CUDA Support
- Environment:Langgenius Dify Python Backend Environment
- Environment:Huggingface Alignment handbook Python Transformers
- Environment:OWASP Www project top 10 for large language model applications GenAI Red Team Environment
- Environment:Pytorch Serve vLLM Engine Environment
- Environment:Ucbepic Docetl Python Runtime
- Environment:Alibaba MNN ARM Mobile Environment
- Environment:LaurentMazare Tch rs Libtorch Build Environment