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== Welcome to {{SITENAME}} == | == Welcome to {{SITENAME}} == | ||
Your | '''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. | |||
'''Connect your AI coding agent.''' Plug Leeroopedia into your favorite coding agent, and let it build robust AI/ML systems autonomously: | |||
* [https://github.com/Leeroo-AI/superml '''SuperML plugin'''] — converts your AI coding agent into an expert ML engineer with agentic memory | |||
* [https://github.com/Leeroo-AI/leeroopedia-mcp '''Leeroopedia MCP'''] — search over best-practices and skills of ML/AI | |||
* [https://github.com/leeroo-ai/kapso '''Kapso'''] — experimentation platform for autonomous AI/ML software building | |||
== Browse by Category == | == Browse by Category == | ||
| Line 11: | Line 44: | ||
! Category !! Description !! Browse | ! Category !! Description !! Browse | ||
|- | |- | ||
| '''Workflows''' || Step-by-step processes and procedures || [[Special:AllPages/Workflow:|Browse All]] | || '''Workflows''' || Step-by-step processes and procedures || [[Special:AllPages/Workflow:|Browse All]] | ||
|- | |- | ||
| '''Principles''' || Core ideas and foundational knowledge || [[Special:AllPages/Principle:|Browse All]] | || '''Principles''' || Core ideas and foundational knowledge || [[Special:AllPages/Principle:|Browse All]] | ||
|- | |- | ||
| '''Implementations''' || Code-level details and modules || [[Special:AllPages/Implementation:|Browse All]] | || '''Implementations''' || Code-level details and modules || [[Special:AllPages/Implementation:|Browse All]] | ||
|- | |- | ||
| '''Heuristics''' || Best practices and guidelines || [[Special:AllPages/Heuristic:|Browse All]] | || '''Heuristics''' || Best practices and guidelines || [[Special:AllPages/Heuristic:|Browse All]] | ||
|- | |- | ||
| '''Environments''' || Setup and configuration guides || [[Special:AllPages/Environment:|Browse All]] | || '''Environments''' || Setup and configuration guides || [[Special:AllPages/Environment:|Browse All]] | ||
|} | |} | ||
== | == Explore Pages == | ||
=== Workflows === | === Workflows === | ||
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=== Principles === | === Principles === | ||
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=== Implementations === | === Implementations === | ||
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=== Heuristics === | === Heuristics === | ||
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=== Environments === | === Environments === | ||
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Latest revision as of 11:45, 14 March 2026
27,667
Total Pages
1,118
Workflows
7,697
Principles
16,832
Implementations
1,245
Heuristics
909
Environments
Welcome to Leeroopedia
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.
Connect your AI coding agent. Plug Leeroopedia into your favorite coding agent, and let it build robust AI/ML systems autonomously:
- SuperML plugin — converts your AI coding agent into an expert ML engineer with agentic memory
- Leeroopedia MCP — search over best-practices and skills of ML/AI
- Kapso — experimentation platform for autonomous AI/ML software building
Browse by Category
| 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 |
Explore Pages
Workflows
- Workflow:HKUDS AI Trader Agent Decision Loop
- Workflow:Anthropics Anthropic sdk python Streaming Message Interaction
- Workflow:Apache Dolphinscheduler Workflow Failover Recovery
- Workflow:Ollama Ollama Model Registry Operations
- Workflow:Infiniflow Ragflow Search Application Setup
- Workflow:PacktPublishing LLM Engineers Handbook Feature Engineering
- Workflow:Promptfoo Promptfoo LLM Evaluation
- Workflow:Dagster io Dagster Dbt Integration
- Workflow:Iterative Dvc Remote Data Sync
- Workflow:PacktPublishing LLM Engineers Handbook LLM Finetuning
Principles
- Principle:Datahub project Datahub Emitter Lifecycle
- Principle:Intel Ipex llm Lookahead Decoding
- Principle:Huggingface Datasets DatasetDict Hub Upload
- Principle:HKUDS AI Trader Benchmark Index Analysis
- Principle:Roboflow Rf detr Object Detection Prediction
- Principle:Mbzuai oryx Awesome LLM Post training Paper Entry Formatting
- Principle:Apache Flink Source Chain Composition
- Principle:Interpretml Interpret Classification Performance Curves
- Principle:Datahub project Datahub Connection Validation
- Principle:Langchain ai Langgraph Task Composition
Implementations
- Implementation:SeleniumHQ Selenium FirefoxProfile
- Implementation:Pyro ppl Pyro NewtonStep
- Implementation:Tencent Ncnn Retinaface Example
- Implementation:Getgauge Taiko RadioButton Element
- Implementation:Evidentlyai Evidently Data Quality Metrics
- Implementation:Truera Trulens Feedback Tool Selection
- Implementation:Sail sg LongSpec MultiMappingDataset
- Implementation:Apache Druid ServicesView
- Implementation:Eventual Inc Daft Utils
- Implementation:Huggingface Diffusers ControlNetModel From Pretrained
Heuristics
- Heuristic:Apache Kafka Coordinator Loading Commit Interval
- Heuristic:Pola rs Polars Streaming For Large Datasets
- Heuristic:Pyro ppl Pyro MCMC Warmup Adaptation
- Heuristic:LLMBook zh LLMBook zh github io BF16 Mixed Precision Default
- Heuristic:ThreeSR Awesome Inference Time Scaling Date Parsing Fallback Tip
- Heuristic:LLMBook zh LLMBook zh github io Reward Model LM Regularization
- Heuristic:Huggingface Trl Distributed Device Map Override
- Heuristic:Huggingface Optimum GPTQ Quantization Defaults
- Heuristic:Langchain ai Langgraph Retry Policy Configuration
- Heuristic:Treeverse LakeFS S3 Multipart Size Constraint
Environments
- Environment:Marker Inc Korea AutoRAG VLLM Environment
- Environment:Huggingface Peft Python Core Dependencies
- Environment:Openclaw Openclaw State Directory And Credentials
- Environment:Openclaw Openclaw Docker Deployment Environment
- Environment:FlagOpen FlagEmbedding GPU Accelerator Environment
- Environment:ArroyoSystems Arroyo Rust Runtime
- Environment:Explodinggradients Ragas Python Runtime Environment
- Environment:Mistralai Client python GCP Deployment Environment
- Environment:LaurentMazare Tch rs Libtorch Build Environment
- Environment:Eventual Inc Daft AI Provider Dependencies