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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 |
Explore Pages
Workflows
- Workflow:InternLM Lmdeploy W8A8 SmoothQuant Quantization
- Workflow:Sktime Pytorch forecasting TFT Hyperparameter Optimization
- Workflow:Dotnet Machinelearning AutoML Experiment
- Workflow:PacktPublishing LLM Engineers Handbook Feature Engineering
- Workflow:Fede1024 Rust rdkafka At Least Once Processing
- Workflow:ChenghaoMou Text dedup SimHash Deduplication
- Workflow:Mlfoundations Open flamingo Data Preparation
- Workflow:Groq Groq python Text To Speech
- Workflow:DataTalksClub Data engineering zoomcamp Docker PostgreSQL Data Ingestion
- Workflow:TobikoData Sqlmesh Dbt project migration
Principles
- Principle:Deepspeedai DeepSpeed AutoTP Engine Init
- Principle:Datajuicer Data juicer Data Selection
- Principle:Webdriverio Webdriverio BrowserStack Extension Management
- Principle:Microsoft Agent framework YAML Agent Loading
- Principle:TobikoData Sqlmesh Data Exploration And Validation
- Principle:Ggml org Llama cpp Chat Template Application
- Principle:Ggml org Ggml Hexagon DSP Computation
- Principle:Langgenius Dify Billing Integration
- Principle:Princeton nlp SimPO Response Post Processing
- Principle:MaterializeInc Materialize Parallel Stress Testing
Implementations
- Implementation:Langchain ai Langchain Git Log Release Notes
- Implementation:Kserve Kserve LocalModel Manager Deployment
- Implementation:Ollama Ollama Llama Graph Header
- Implementation:Zai org CogVideo CogVideoXI2VPipeline Call
- Implementation:Apache Flink Mapreduce HadoopInputFormat
- Implementation:Puppeteer Puppeteer HTTPResponse
- Implementation:Ggml org Llama cpp Perplexity Evaluation
- Implementation:Ggml org Llama cpp Preset
- Implementation:Recommenders team Recommenders Standard VAE
- Implementation:Unslothai Unsloth GEMM Autotuning Configs
Heuristics
- Heuristic:Protectai Llm guard Token Limit Early Guard
- Heuristic:Langchain ai Langchain Warning Deprecated AnthropicLLM
- Heuristic:Alibaba MNN NC4HW4 Data Layout
- Heuristic:Langchain ai Langchain Retry Scope Best Practice
- Heuristic:Anthropics Anthropic sdk python Model Deprecation Awareness
- Heuristic:Microsoft Semantic kernel Custom HttpClient Retry Policy
- Heuristic:Pytorch Serve Torch Compile Best Practices
- Heuristic:Haotian liu LLaVA Quantization MM Projector Exclusion
- Heuristic:Alibaba MNN Memory Mode Selection
- Heuristic:AnswerDotAI RAGatouille Collection Size Index Tuning
Environments
- Environment:Online ml River Python Runtime Environment
- Environment:CrewAIInc CrewAI LLM Provider Credentials
- Environment:TobikoData Sqlmesh BigQuery Connection
- Environment:Avdvg InjectGuard CUDA GPU
- Environment:Scikit learn contrib Imbalanced learn Keras TensorFlow
- Environment:Mbzuai oryx Awesome LLM Post training Git CLI
- Environment:NVIDIA NeMo Aligner TensorRT LLM Acceleration Environment
- Environment:VainF Torch Pruning LLM Pruning Dependencies
- Environment:Tensorflow Serving Kubernetes Deployment Environment
- Environment:Pytorch Serve Distributed Training Environment