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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:Nautechsystems Nautilus trader Backtest with BacktestEngine
- Workflow:Kubeflow Pipelines XGBoost Training Pipeline
- Workflow:Truera Trulens Custom App Instrumentation And Evaluation
- Workflow:Diagram of thought Diagram of thought DoT Trace Extraction
- Workflow:Princeton nlp SimPO SimPO Training
- Workflow:PrefectHQ Prefect Dbt Model Orchestration
- Workflow:Lance format Lance Dataset Lifecycle
- Workflow:Vibrantlabsai Ragas Custom Metric Creation
- Workflow:VainF Torch Pruning Vision Transformer Pruning
- Workflow:Open compass VLMEvalKit Video Benchmark Evaluation
Principles
- Principle:Unstructured IO Unstructured Basic Chunking
- Principle:Bentoml BentoML Model Persistence
- Principle:TobikoData Sqlmesh Backfill Strategy Selection
- Principle:Scikit learn contrib Imbalanced learn Random Under Sampling Boosting
- Principle:Bitsandbytes foundation Bitsandbytes 4bit Quantization Configuration
- Principle:LaurentMazare Tch rs REINFORCE Policy Gradient
- Principle:Datahub project Datahub Patch Based Updates
- Principle:Bentoml BentoML Service Architecture Design
- Principle:Tencent Ncnn Python Bindings Build
- Principle:OWASP Www project top 10 for large language model applications Entry Refinement and Revoting
Implementations
- Implementation:Microsoft Semantic kernel ContactsPlugin OpenAPI
- Implementation:Microsoft LoRA Lora State Dict
- Implementation:Kubeflow Pipelines Helm Cache Template
- Implementation:Alibaba MNN Protobuf Wire Format Lite CC
- Implementation:NVIDIA TransformerEngine ONNX Extensions
- Implementation:Helicone Helicone BaseProvider
- Implementation:Alibaba MNN ExecutorScope
- Implementation:Microsoft LoRA Run Chinese Ref
- Implementation:Datajuicer Data juicer CsvFormatter
- Implementation:InternLM Lmdeploy Gemm Kernel
Heuristics
- Heuristic:Openai Evals Thread Tuning
- Heuristic:Princeton nlp Tree of thought llm Value Caching
- Heuristic:Langgenius Dify Token Refresh Loop Prevention
- Heuristic:Roboflow Rf detr EMA Best Checkpoint Strategy
- Heuristic:Junyanz Pytorch CycleGAN and pix2pix High Res Crop Training
- Heuristic:Datahub project Datahub Validation Across All APIs
- Heuristic:OpenRLHF OpenRLHF Adam Offload Memory Tip
- Heuristic:OpenBMB UltraFeedback Score 10 Anomaly Correction
- Heuristic:NVIDIA DALI Thread Affinity Optimization
- Heuristic:ChenghaoMou Text dedup False Positive Verification Tradeoff
Environments
- Environment:Vllm project Vllm CUDA Runtime
- Environment:PacktPublishing LLM Engineers Handbook VLLM Evaluation Environment
- Environment:Onnx Onnx Python Runtime Environment
- Environment:Alibaba MNN GPU Metal Environment
- Environment:Mit han lab Llm awq Flash Attention Environment
- Environment:NVIDIA NeMo Curator Video Codec Stack
- Environment:Promptfoo Promptfoo SQLite Database
- Environment:Vllm project Vllm Environment Variables
- Environment:ContextualAI HALOs CUDA 12 1 Training Environment
- Environment:SqueezeAILab ETS Multi GPU Sglang Runtime