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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:LMCache LMCache KV Cache Offloading
- Workflow:Microsoft Playwright End to end test authoring
- Workflow:PeterL1n BackgroundMattingV2 Model export
- Workflow:Langchain ai Langchain Streaming Responses
- Workflow:Gretelai Gretel synthetics ACTGAN Tabular Synthesis
- Workflow:NVIDIA DALI Custom Operator Development
- Workflow:Huggingface Datasets Dataset Streaming
- Workflow:Apache Spark Standalone Cluster Deployment
- Workflow:Scikit learn contrib Imbalanced learn Ensemble Imbalanced Classification
- Workflow:Deepset ai Haystack Document Indexing Pipeline
Principles
- Principle:Googleapis Python genai Cache Creation
- Principle:Puppeteer Puppeteer Browser Launching
- Principle:Ggml org Ggml Model Quantization
- Principle:Cleanlab Cleanlab Spurious Correlation Analysis
- Principle:OpenHands OpenHands Progress Notification
- Principle:Apache Paimon Target Table Preparation
- Principle:Online ml River Online Covariance Estimation
- Principle:SqueezeAILab ETS Dependency Installation
- Principle:Apache Shardingsphere YAML Configuration Definition
- Principle:Mlc ai Web llm Tool Call Extraction
Implementations
- Implementation:Mistralai Client python GCP ChatCompletionRequest
- Implementation:Online ml River Preprocessing StandardScaler
- Implementation:TobikoData Sqlmesh Modal
- Implementation:Bentoml BentoML CLI Env
- Implementation:BerriAI Litellm Sensitive Data Masker
- Implementation:EvolvingLMMs Lab Lmms eval Padding Requests
- Implementation:Open compass VLMEvalKit TEDS Metric
- Implementation:Openai Openai agents python RunResult To State
- Implementation:Spotify Luigi Mustache Templating
- Implementation:NVIDIA NeMo Curator FLEURS Manifest Stage
Heuristics
- Heuristic:Google deepmind Mujoco Solver Selection Guide
- Heuristic:Ggml org Llama cpp Warning Deprecated Legacy Converters
- Heuristic:Hpcaitech ColossalAI Empty Cache Between Phases
- Heuristic:Danijar Dreamerv3 Free Nats KL Thresholding
- Heuristic:Lucidrains X transformers Gradient Clipping And Accumulation
- Heuristic:Run llama Llama index Batch Eval Retry Strategy
- Heuristic:Lance format Lance IO Buffer And Batch Sizing
- Heuristic:Sail sg LongSpec TF32 And FP16 Training
- Heuristic:Astronomer Astronomer cosmos Static Parser Hang Workaround
- Heuristic:SeldonIO Seldon core Model Scheduling Preference Tip
Environments
- Environment:Axolotl ai cloud Axolotl CUDA GPU
- Environment:Apache Flink Python PyFlink Environment
- Environment:Ucbepic Docetl Frontend Node Environment
- Environment:Neuml Txtai Python Core Dependencies
- Environment:FlowiseAI Flowise Docker Environment
- Environment:Kserve Kserve Gateway API
- Environment:Confident ai Deepeval Python 3 9 Runtime
- Environment:ArroyoSystems Arroyo Kubernetes Deployment
- Environment:Rapidsai Cuml CUDA GPU
- Environment:Openai CLIP Python Dependencies