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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.
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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 |
Explore Pages
Workflows
- Workflow:Dagster io Dagster DSPy Optimization
- Workflow:Cohere ai Cohere python Chat Completion
- Workflow:Tensorflow Serving Batched Inference Pipeline
- Workflow:Infiniflow Ragflow Document Processing Pipeline
- Workflow:TobikoData Sqlmesh Environment management
- Workflow:Avdvg InjectGuard Vector Similarity Detection Pipeline
- Workflow:Dagster io Dagster Modal Serverless Pipeline
- Workflow:Eventual Inc Daft Data Lakehouse ETL
- Workflow:Haifengl Smile SQL Analytics Pipeline
- Workflow:OpenRLHF OpenRLHF Reward Model Training
Principles
- Principle:Bentoml BentoML Model Cleanup
- Principle:NVIDIA TransformerEngine Fused Attention
- Principle:Neuml Txtai RAG Index Building
- Principle:Mage ai Mage ai Record Validation and Batching
- Principle:ClickHouse ClickHouse Compile Time Reflection
- Principle:Dotnet Machinelearning Binary Classification Training
- Principle:Lm sys FastChat Leaderboard Dashboard Rendering
- Principle:Mage ai Mage ai HTTP Client Request
- Principle:Microsoft LoRA LoRA Weight Extraction
- Principle:VainF Torch Pruning LLM Perplexity Evaluation
Implementations
- Implementation:Scikit learn Scikit learn StandardScaler Init
- Implementation:Vllm project Vllm Machete Generate
- Implementation:Protectai Llm guard Input InvisibleText
- Implementation:Mlc ai Mlc llm MoE Misc
- Implementation:Microsoft Autogen Studio Auth Routes
- Implementation:Rapidsai Cuml Ranking Metrics
- Implementation:Google deepmind Mujoco Engine Derivative FD
- Implementation:Norrrrrrr lyn WAInjectBench SentenceTransformer Encode
- Implementation:Turboderp org Exllamav2 ExLlamaV2TokenizerBase
- Implementation:Microsoft Semantic kernel Kernel CreateBuilder
Heuristics
- Heuristic:Avhz RustQuant Learning Rate Tuning
- Heuristic:Scikit learn contrib Imbalanced learn Sparse Matrix Handling
- Heuristic:Iamhankai Forest of Thought Early Stop Majority Vote
- Heuristic:Arize ai Phoenix Notebook Event Loop Patching
- Heuristic:Volcengine Verl FSDP Mixed Precision Init
- Heuristic:Vespa engine Vespa RPM Zstd Compression Settings
- Heuristic:Sail sg LongSpec Triton Block Size Tuning
- Heuristic:Deepset ai Haystack Logging Auto Detection
- Heuristic:SeldonIO Seldon core Autoscaling Dual Config Tip
- Heuristic:Microsoft Agent framework Silent Workflow Failures
Environments
- Environment:Nightwatchjs Nightwatch Selenium WebDriver 4
- Environment:Google deepmind Dm control Python MuJoCo Runtime
- Environment:Vespa engine Vespa Cosign Sigstore Signing
- Environment:Groq Groq python Python Groq SDK
- Environment:BerriAI Litellm PostgreSQL Database
- Environment:NVIDIA DALI PyTorch Environment
- Environment:Apache Shardingsphere Etcd Cluster Coordination
- Environment:Hiyouga LLaMA Factory Distributed Training Environment
- Environment:Huggingface Transformers Python 310 Runtime
- Environment:Dotnet Machinelearning Native Build Toolchain