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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 |
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Workflows
- Workflow:DataTalksClub Data engineering zoomcamp dbt Analytics Transformation
- Workflow:Obss Sahi COCO Evaluation
- Workflow:Openai CLIP Prompt engineered classification
- Workflow:NVIDIA TransformerEngine FSDP Distributed Training
- Workflow:Huggingface Peft LoRA Embedding Semantic Search
- Workflow:Scikit learn Scikit learn Data Preprocessing Pipeline
- Workflow:Dagster io Dagster DSPy Optimization
- Workflow:Pola rs Polars SQL Query Interface
- Workflow:Unslothai Unsloth Vision Model Finetuning
- Workflow:VainF Torch Pruning Vision Transformer Pruning
Principles
- Principle:PrefectHQ Prefect HTTP Data Extraction
- Principle:Sgl project Sglang Multimodal Prompt Construction
- Principle:Interpretml Interpret SHAP Kernel Explanation
- Principle:Mlc ai Web llm Text Completion Configuration
- Principle:Datahub project Datahub Emitter Initialization
- Principle:Dagster io Dagster Run Configuration
- Principle:Norrrrrrr lyn WAInjectBench Supervised Training Loop
- Principle:CARLA simulator Carla CMake Build Configuration
- Principle:Vespa engine Vespa Log Target and Level Configuration
- Principle:Marker Inc Korea AutoRAG Document Chunking
Implementations
- Implementation:Online ml River Compat RiverToSklearn
- Implementation:Recommenders team Recommenders DKN Iterator
- Implementation:Lance format Lance Commit Compaction
- Implementation:ArroyoSystems Arroyo Kubernetes Scheduler
- Implementation:Haosulab ManiSkill PDJointPosController
- Implementation:Open compass VLMEvalKit VGRPBench StarBattle
- Implementation:Sgl project Sglang FA4 Interface
- Implementation:Open compass VLMEvalKit QwenVL
- Implementation:Cypress io Cypress Reporter Component CT
- Implementation:Vibrantlabsai Ragas RougeScore
Heuristics
- Heuristic:Ollama Ollama Multimodal Parallel Restriction
- Heuristic:Vllm project Vllm GPU Memory Utilization Tuning
- Heuristic:Allenai Open instruct BFloat16 Training
- Heuristic:Tensorflow Serving Model Warmup Strategy
- Heuristic:Facebookresearch Audiocraft Codebook Dead Code Expiration
- Heuristic:Hiyouga LLaMA Factory Gradient Checkpointing Memory Optimization
- Heuristic:ContextualAI HALOs Online Round Budgeting
- Heuristic:PrefectHQ Prefect Retry Backoff Strategy
- Heuristic:Haotian liu LLaVA Tokenizer Version Offset Correction
- Heuristic:Turboderp org Exllamav2 Quantization Conversion Tips
Environments
- Environment:LMCache LMCache Python Runtime
- Environment:Alibaba MNN Python Export Environment
- Environment:Fastai Fastbook Python FastAI Environment
- Environment:Vllm project Vllm Benchmarks
- Environment:Astronomer Astronomer cosmos Python Airflow Runtime
- Environment:Kserve Kserve VLLM Runtime
- Environment:Scikit learn contrib Imbalanced learn Keras TensorFlow
- Environment:Kornia Kornia ONNX Runtime Environment
- Environment:Facebookresearch Habitat lab Python 3 9 Core Dependencies
- Environment:Vllm project Vllm CUDA Hopper