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== Welcome to {{SITENAME}} == | |||
'''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. | |||
* [https:// | |||
* [https:// | 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. | ||
* [https:// | |||
'''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 == | |||
{| class="wikitable" style="width:100%" | |||
|- | |||
! Category !! Description !! Browse | |||
|- | |||
|| '''Workflows''' || Step-by-step processes and procedures || [[Special:AllPages/Workflow:|Browse All]] | |||
|- | |||
|| '''Principles''' || Core ideas and foundational knowledge || [[Special:AllPages/Principle:|Browse All]] | |||
|- | |||
|| '''Implementations''' || Code-level details and modules || [[Special:AllPages/Implementation:|Browse All]] | |||
|- | |||
|| '''Heuristics''' || Best practices and guidelines || [[Special:AllPages/Heuristic:|Browse All]] | |||
|- | |||
|| '''Environments''' || Setup and configuration guides || [[Special:AllPages/Environment:|Browse All]] | |||
|} | |||
== Explore Pages == | |||
=== Workflows === | |||
{{#cargo_query:tables=PageInfo|fields=_pageName|where=PageType='Workflow'|order by=RAND()|limit=10|format=ul}} | |||
=== Principles === | |||
{{#cargo_query:tables=PageInfo|fields=_pageName|where=PageType='Principle'|order by=RAND()|limit=10|format=ul}} | |||
=== Implementations === | |||
{{#cargo_query:tables=PageInfo|fields=_pageName|where=PageType='Implementation'|order by=RAND()|limit=10|format=ul}} | |||
=== Heuristics === | |||
{{#cargo_query:tables=PageInfo|fields=_pageName|where=PageType='Heuristic'|order by=RAND()|limit=10|format=ul}} | |||
=== Environments === | |||
{{#cargo_query:tables=PageInfo|fields=_pageName|where=PageType='Environment'|order by=RAND()|limit=10|format=ul}} | |||
Latest revision as of 11:45, 14 March 2026
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:PeterL1n BackgroundMattingV2 Realtime webcam matting
- Workflow:Fede1024 Rust rdkafka Async Stream Processing
- Workflow:Confident ai Deepeval Synthetic Dataset Generation
- Workflow:ARISE Initiative Robosuite Teleoperation
- Workflow:Vibrantlabsai Ragas Testset Generation
- Workflow:Haosulab ManiSkill Imitation Learning Pipeline
- Workflow:Gretelai Gretel synthetics ACTGAN Tabular Synthesis
- Workflow:Explodinggradients Ragas Metric Prompt Optimization
- Workflow:InternLM Lmdeploy LLM Offline Batch Inference
- Workflow:Lm sys FastChat Vicuna SFT Finetuning
Principles
- Principle:PrefectHQ Prefect Frontend Application Configuration
- Principle:Apache Airflow Scheduling Configuration
- Principle:NVIDIA TransformerEngine Comm GEMM Overlap
- Principle:Webdriverio Webdriverio ElementChaining
- Principle:Haotian liu LLaVA Model Loading
- Principle:FMInference FlexLLMGen Distributed Process Launching
- Principle:TobikoData Sqlmesh Interval Configuration
- Principle:ClickHouse ClickHouse Core Compiler Macros
- Principle:Kubeflow Kubeflow Tune Hyperparameters
- Principle:Bentoml BentoML Model Cloud Sync
Implementations
- Implementation:Open compass VLMEvalKit VisFactor
- Implementation:Hpcaitech ColossalAI RLVRRewardModel
- Implementation:Huggingface Trl RewardTrainer Init Train
- Implementation:Lance format Lance NamespaceSchema
- Implementation:PeterL1n BackgroundMattingV2 ZipDataset
- Implementation:Mlflow Mlflow Trace Decorator
- Implementation:Facebookresearch Habitat lab XRInput
- Implementation:Vibrantlabsai Ragas Text2SQL Data Utils
- Implementation:Haosulab ManiSkill Humanoid
- Implementation:Microsoft Semantic kernel Agent Kernel Plugins Add
Heuristics
- Heuristic:Tensorflow Tfjs WebGL Shader Warmup
- Heuristic:Volcengine Verl Sequence Length Balancing
- Heuristic:TobikoData Sqlmesh Snapshot TTL Defaults
- Heuristic:Zai org CogVideo Memory Optimization Strategies
- Heuristic:Cohere ai Cohere python Pydantic V1 V2 Compatibility
- Heuristic:MarketSquare Robotframework browser Shared Node Process For Parallel
- Heuristic:Truera Trulens Feedback Score Thresholds
- Heuristic:LLMBook zh LLMBook zh github io BF16 Mixed Precision Default
- Heuristic:Helicone Helicone Anthropic Cache Double Count Prevention
- Heuristic:Huggingface Datasets Flatten Indices Performance
Environments
- Environment:Vespa engine Vespa Cosign Sigstore Signing
- Environment:Microsoft Agent framework Core Package Dependencies
- Environment:Haotian liu LLaVA Python CUDA Training Environment
- Environment:Webdriverio Webdriverio Cloud Service Credentials
- Environment:Axolotl ai cloud Axolotl Python Runtime
- Environment:Tensorflow Tfjs Browser Runtime
- Environment:BerriAI Litellm Docker Deployment
- Environment:BerriAI Litellm Observability Stack
- Environment:CrewAIInc CrewAI Python Runtime Environment
- Environment:Apache Shardingsphere Java Runtime Environment