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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:Mlflow Mlflow Model Logging and Registry
- Workflow:Evidentlyai Evidently Text Data Quality Evaluation
- Workflow:PeterL1n BackgroundMattingV2 Training pipeline
- Workflow:Kornia Kornia Edge Detection Pipeline
- Workflow:Dagster io Dagster ETL Pipeline
- Workflow:Ggml org Ggml GPT2 Text Generation
- Workflow:Eventual Inc Daft Distributed UDF Processing
- Workflow:OpenRLHF OpenRLHF PPO Ray Training
- Workflow:Helicone Helicone LLM Request Proxy Logging
- Workflow:Datahub project Datahub Java SDK V2 Entity Management
Principles
- Principle:Apache Paimon Table Writing
- Principle:Heibaiying BigData Notes HBase Table Creation
- Principle:Scikit learn Scikit learn Search Execution
- Principle:Intel Ipex llm RAG With LlamaIndex
- Principle:Ray project Ray Cross Language Task Submission
- Principle:Microsoft Semantic kernel Vector Store Data Model
- Principle:Microsoft Autogen Message Filtering
- Principle:Datahub project Datahub Pipeline Execution
- Principle:Cohere ai Cohere python Streaming Chat Request
- Principle:Microsoft DeepSpeedExamples Model Evaluation And Export
Implementations
- Implementation:Lance format Lance LegacyPhysicalDispatch
- Implementation:Sgl project Sglang Quick AllReduce
- Implementation:Online ml River Neighbors KNNRegressor
- Implementation:LaurentMazare Tch rs ModuleT Forward T
- Implementation:Apache Airflow Metrics Template
- Implementation:OpenGVLab InternVL InternVisionConfig
- Implementation:Apache Paimon FunctionChange
- Implementation:Avhz RustQuant Barrier Backend
- Implementation:Openai Openai python Input Tokens Count
- Implementation:ArroyoSystems Arroyo Redis Lookup
Heuristics
- Heuristic:SeldonIO Seldon core Tracing Latency Tip
- Heuristic:Datajuicer Data juicer Checkpoint Resumption Strategy
- Heuristic:Wandb Weave Batch Processing Tuning
- Heuristic:Trailofbits Fickling Allowlist Maintenance
- Heuristic:Unslothai Unsloth Merge Memory Management
- Heuristic:MarketSquare Robotframework browser Shared Node Process For Parallel
- Heuristic:Deepspeedai DeepSpeed Shared Memory Sizing
- Heuristic:Apache Hudi Data Skipping Limitations
- Heuristic:Pola rs Polars Streaming For Large Datasets
- Heuristic:Fastai Fastbook Embedding Size Rule
Environments
- Environment:Pyro ppl Pyro Distributed Training
- Environment:Online ml River Python Runtime Environment
- Environment:Turboderp org Exllamav2 Build Toolchain
- Environment:Togethercomputer Together python Python SDK Runtime
- Environment:Ollama Ollama GPU Runtime
- Environment:Huggingface Alignment handbook Python TRL
- Environment:Kserve Kserve Kubernetes Cluster
- Environment:Webdriverio Webdriverio Cloud Service Credentials
- Environment:Predibase Lorax Docker Container Runtime
- Environment:Microsoft LoRA NLU Conda Environment