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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:Vibrantlabsai Ragas RAG Evaluation
- Workflow:Dotnet Machinelearning Text Classification
- Workflow:Elevenlabs Elevenlabs python Text to Speech Generation
- Workflow:Princeton nlp Tree of thought llm Adding new task
- Workflow:AUTOMATIC1111 Stable diffusion webui Image to image generation
- Workflow:DataExpert io Data engineer handbook AB Experimentation Server
- Workflow:Openai Openai node Structured Output Parsing
- Workflow:Haifengl Smile SQL Analytics Pipeline
- Workflow:TobikoData Sqlmesh Dbt project migration
- Workflow:Intel Ipex llm QLoRA Finetuning
Principles
- Principle:Unstructured IO Unstructured PDF Partitioning
- Principle:Haifengl Smile SQL Metadata Exploration
- Principle:Ray project Ray Multi Language Cluster Initialization
- Principle:Vespa engine Vespa CPP Compilation
- Principle:MarketSquare Robotframework browser Plugin Architecture
- Principle:Ray project Ray Actor Termination
- Principle:Snorkel team Snorkel Labeling Function Analysis
- Principle:Volcengine Verl GAE Advantage Estimation
- Principle:FlowiseAI Flowise Node Registry Loading
- Principle:Ggml org Llama cpp Distributed Inference
Implementations
- Implementation:Sktime Pytorch forecasting Baseline
- Implementation:Langfuse Langfuse CreateExperimentJobClickhouse
- Implementation:Microsoft Onnxruntime LazyTensorFusion
- Implementation:Zai org CogVideo SAT Get Model Load Checkpoint
- Implementation:EvolvingLMMs Lab Lmms eval Cache Utils
- Implementation:ArroyoSystems Arroyo Create Profile Page
- Implementation:Puppeteer Puppeteer ResolveBuildId
- Implementation:Haosulab ManiSkill SceneManipulationEnv
- Implementation:Lance format Lance Java DynamicContextProvider
- Implementation:AUTOMATIC1111 Stable diffusion webui UniPC Sampler
Heuristics
- Heuristic:Microsoft Agent framework Tool Approval Mode Production
- Heuristic:Iamhankai Forest of Thought Input Length Overflow Recovery
- Heuristic:Dagster io Dagster Record Over Dataclass
- Heuristic:NVIDIA NeMo Curator GPU Memory Resource Allocation
- Heuristic:Huggingface Open r1 vLLM GPU Allocation
- Heuristic:Huggingface Trl Disable Dropout For RL Training
- Heuristic:Ggml org Ggml Thread Count Selection
- Heuristic:CARLA simulator Carla Client Server Version Match
- Heuristic:Rapidsai Cuml Dask Data Partitioning
- Heuristic:Huggingface Trl Distributed Device Map Override
Environments
- Environment:Pytorch Serve Distributed Training Environment
- Environment:Groq Groq python Python Groq SDK
- Environment:Vllm project Vllm CUDA
- Environment:Datajuicer Data juicer Python Runtime Environment
- Environment:Huggingface Datasets Lance Dependencies
- Environment:OpenBMB UltraFeedback OpenAI API Environment
- Environment:Google deepmind Dm control GLFW Desktop Rendering
- Environment:Mlflow Mlflow GPU System Metrics Environment
- Environment:PacktPublishing LLM Engineers Handbook API Credentials
- Environment:Huggingface Datasets Python PyArrow Core