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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:Dagster io Dagster ETL Pipeline
- Workflow:Microsoft Autogen Multi Agent Conversation
- Workflow:Nightwatchjs Nightwatch E2E Test Authoring
- Workflow:Rapidsai Cuml GPU Clustering
- Workflow:Vibrantlabsai Ragas Prompt Optimization
- Workflow:Huggingface Datatrove Common Crawl Processing
- Workflow:Lance format Lance Version Management
- Workflow:NVIDIA DALI Image Classification Training PyTorch
- Workflow:Huggingface Peft LoRA Embedding Semantic Search
- Workflow:Openai Openai agents python Streaming Agent Execution
Principles
- Principle:Groq Groq python Message Construction
- Principle:Fastai Fastbook Backpropagation
- Principle:ChenghaoMou Text dedup LSH Banding And Clustering
- Principle:Langchain ai Langgraph Development Server
- Principle:Anthropics Anthropic sdk python API Request Execution
- Principle:Puppeteer Puppeteer CDP Session Management
- Principle:Langgenius Dify Processing Node Configuration
- Principle:Online ml River SNARIMAX Forecasting
- Principle:Pytorch Serve Accelerate Device Mapping
- Principle:Fastai Fastbook Model Interpretation
Implementations
- Implementation:SeleniumHQ Selenium Python Conftest
- Implementation:TobikoData Sqlmesh Context Run
- Implementation:Ggml org Llama cpp Jinja Caps Header
- Implementation:Vllm project Vllm Test Pipeline Config
- Implementation:FMInference FlexLLMGen Batch Query Test
- Implementation:Langchain ai Langchain Langchain Classic Init
- Implementation:Marker Inc Korea AutoRAG Raw And Corpus Schema
- Implementation:Microsoft Semantic kernel AddOpenAIChatClient
- Implementation:Langgenius Dify Annotation Service
- Implementation:AUTOMATIC1111 Stable diffusion webui Hypertile Optimization
Heuristics
- Heuristic:Anthropics Anthropic sdk python Retry Backoff Strategy
- Heuristic:Apache Spark Hardware Provisioning Tips
- Heuristic:Kserve Kserve Server Side Apply For CRDs
- Heuristic:Eventual Inc Daft Delta Lake S3 Locking
- Heuristic:SqueezeAILab ETS Thread Parallelism Suppression
- Heuristic:Mlc ai Web llm Low Resource Model Selection
- Heuristic:Vllm project Vllm GPU Memory Utilization Tuning
- Heuristic:Langgenius Dify Workflow Draft Hash Sync
- Heuristic:NVIDIA TransformerEngine FP8 Recipe Auto Selection
- Heuristic:Protectai Llm guard ONNX Runtime Optimization
Environments
- Environment:Anthropics Anthropic sdk python Azure Foundry Environment
- Environment:Unstructured IO Unstructured Profiling Tools
- Environment:DataExpert io Data engineer handbook Python Development Environment
- Environment:Mistralai Client python Realtime Transcription Environment
- Environment:Deepseek ai Janus JanusFlow Diffusers Environment
- Environment:Hpcaitech ColossalAI GRPO Distributed Environment
- Environment:BerriAI Litellm Redis Cache Backend
- Environment:Apache Druid Integration Test Docker
- Environment:Mage ai Mage ai Python 3 9 Runtime
- Environment:LMCache LMCache CUDA GPU Runtime