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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 |
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Workflows
- Workflow:Eventual Inc Daft Multimodal AI Batch Inference
- Workflow:Langfuse Langfuse Batch export pipeline
- Workflow:NVIDIA DALI Custom Operator Development
- Workflow:Bentoml BentoML Service Definition And Local Serving
- Workflow:Microsoft Playwright Network mocking and interception
- Workflow:CarperAI Trlx PPO Sentiment Training
- Workflow:Neuml Txtai Model Training
- Workflow:Scikit learn Scikit learn Ensemble Model Building
- Workflow:FlowiseAI Flowise Agentflow V2 Creation
- Workflow:Turboderp org Exllamav2 Interactive Chat
Principles
- Principle:Ollama Ollama GGUF Model Conversion Mistral
- Principle:Apache Paimon Indexed Split Result Retrieval
- Principle:Wandb Weave Decorator Style Enforcement
- Principle:Mage ai Mage ai Incremental Sync State
- Principle:Apache Kafka JVM Classpath Assembly
- Principle:Googleapis Python genai Image Result Processing
- Principle:Puppeteer Puppeteer Screenshot Capture
- Principle:Apache Flink Cross Source Checkpointing
- Principle:Mit han lab Llm awq Weight Clipping Optimization
- Principle:Datajuicer Data juicer Partition Size Optimization
Implementations
- Implementation:Apache Beam WindmillStateInternals Persist
- Implementation:Scikit learn Scikit learn NumpyDocScrape
- Implementation:Speechbrain Speechbrain Prepare PeoplesSpeech
- Implementation:Rapidsai Cuml MBSGDClassifier
- Implementation:Microsoft Autogen Component Schema Gen
- Implementation:Ucbepic Docetl BookmarksPanel
- Implementation:Microsoft Autogen CI Checks Workflow
- Implementation:PrefectHQ Prefect Materialize Decorator
- Implementation:Deepspeedai DeepSpeed Evoformer Bias Broadcast
- Implementation:EvolvingLMMs Lab Lmms eval Padding Requests
Heuristics
- Heuristic:Snorkel team Snorkel DataParallel Default Behavior
- Heuristic:Fastai Fastbook Embedding Size Rule
- Heuristic:Princeton nlp Tree of thought llm Ad Hoc Value Map Scoring
- Heuristic:Arize ai Phoenix Adaptive Rate Limiting
- Heuristic:Mit han lab Llm awq Kernel Selection Thresholds
- Heuristic:Obss Sahi Confidence Threshold Setting
- Heuristic:Snorkel team Snorkel Binary Only Slicing
- Heuristic:ChenghaoMou Text dedup SimHash Optimization Ceiling
- Heuristic:Ucbepic Docetl Reduce Parallel Fold Tuning
- Heuristic:Arize ai Phoenix Environment Variable Precedence
Environments
- Environment:PrefectHQ Prefect Prefect Server Database
- Environment:Ray project Ray Java Build Environment
- Environment:Dagster io Dagster PostgreSQL Storage
- Environment:Infiniflow Ragflow Python Runtime
- Environment:VainF Torch Pruning PyTorch Python Core
- Environment:OpenBMB UltraFeedback vLLM Multi GPU Environment
- Environment:Eventual Inc Daft Ray Distributed Runner
- Environment:Speechbrain Speechbrain Multi GPU DDP
- Environment:Diagram of thought Diagram of thought Python Graph Libraries
- Environment:TobikoData Sqlmesh Python Runtime