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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:Microsoft BIPIA White Box Defense Finetuning
- Workflow:Apache Hudi Flink Schema Evolution
- Workflow:PeterL1n BackgroundMattingV2 Realtime webcam matting
- Workflow:Rapidsai Cuml Random Forest Training And Inference
- Workflow:Langchain ai Langgraph ReAct Agent Creation
- Workflow:EvolvingLMMs Lab Lmms eval Custom Model Integration
- Workflow:TobikoData Sqlmesh Github CICD automation
- Workflow:PrefectHQ Prefect Per Worker Task Concurrency
- Workflow:Ggml org Llama cpp Interactive Chat
- Workflow:Lance format Lance Vector Search Pipeline
Principles
- Principle:Rapidsai Cuml Synthetic Dataset Generation
- Principle:Fastai Fastbook Model Interpretation
- Principle:InternLM Lmdeploy Pytorch Engine Configuration
- Principle:Roboflow Rf detr Finetuned Model Loading
- Principle:Neuml Txtai Agent Embeddings Database
- Principle:Tensorflow Tfjs Normalization Techniques
- Principle:Pytorch Serve LLM Text Generation
- Principle:Ollama Ollama ServerArchitecture
- Principle:Nightwatchjs Nightwatch Extension Path Configuration
- Principle:Huggingface Datasets Work Sharding
Implementations
- Implementation:Langgenius Dify UseMetadata
- Implementation:Recommenders team Recommenders BaseModel Run Eval
- Implementation:Speechbrain Speechbrain Prepare ESC50 Interpret
- Implementation:Online ml River Cluster CluStream
- Implementation:Online ml River Preprocessing FeatureHasher
- Implementation:Astronomer Astronomer cosmos Task Dependency Wiring
- Implementation:Vibrantlabsai Ragas MetricBasePrompt
- Implementation:Pytorch Serve BasePippyHandler
- Implementation:Heibaiying BigData Notes Spark Write External Data
- Implementation:Huggingface Datasets PyTorch DataLoader
Heuristics
- Heuristic:Mlc ai Web llm Tokenizer JSON Preference
- Heuristic:Lucidrains X transformers Rotary Position Embedding Selection
- Heuristic:Obss Sahi Class Agnostic vs Per Class NMS
- Heuristic:Haotian liu LLaVA Gradient Checkpointing Memory Optimization
- Heuristic:Sgl project Sglang Chunked Prefill OOM Prevention
- Heuristic:Deepseek ai Janus Bfloat16 Operation Workarounds
- Heuristic:Risingwavelabs Risingwave LSM Compaction Tuning
- Heuristic:Kubeflow Kubeflow Issue Routing To Sub Repos
- Heuristic:BerriAI Litellm Retry Backoff Strategy
- Heuristic:Getgauge Taiko Navigation Wait Strategy
Environments
- Environment:Huggingface Datatrove Processing Dependencies
- Environment:Microsoft BIPIA Python CUDA GPU Environment
- Environment:Farama Foundation Gymnasium Box2D Physics Backend
- Environment:OpenGVLab InternVL PEFT LoRA
- Environment:ArroyoSystems Arroyo PostgreSQL Database
- Environment:HKUDS AI Trader Browser Runtime
- Environment:Nightwatchjs Nightwatch BrowserStack Cloud
- Environment:Duckdb Duckdb CMake Build Toolchain
- Environment:Snorkel team Snorkel PySpark
- Environment:Openai Openai node Node 20 Runtime