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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:Lance format Lance Dataset Lifecycle
- Workflow:CrewAIInc CrewAI Flow Based Orchestration
- Workflow:Interpretml Interpret EBM Model Export
- Workflow:Getgauge Taiko Gauge Integration Testing
- Workflow:Huggingface Open r1 Model Evaluation
- Workflow:SeldonIO Seldon core HuggingFace Model Serving
- Workflow:Huggingface Diffusers DreamBooth Personalization
- Workflow:EvolvingLMMs Lab Lmms eval Custom Task Creation
- Workflow:ClickHouse ClickHouse Building From Source
- Workflow:Microsoft Playwright Network mocking and interception
Principles
- Principle:Shiyu coder Kronos Model Loading
- Principle:Infiniflow Ragflow Search Result Display
- Principle:Triton inference server Server Model Configuration
- Principle:FMInference FlexLLMGen Baseline Benchmark Orchestration
- Principle:Farama Foundation Gymnasium Environment Validation
- Principle:Microsoft Semantic kernel Process Framework Frontend
- Principle:Huggingface Peft Adapter Injection
- Principle:ContextualAI HALOs Bradley Terry Reward Modeling
- Principle:Microsoft DeepSpeedExamples Model Evaluation And Export
- Principle:Huggingface Datatrove Pipeline Step Abstraction
Implementations
- Implementation:Online ml River Datasets Bikes
- Implementation:Vibrantlabsai Ragas EvaluationDataset From List
- Implementation:Mbzuai oryx Awesome LLM Post training Fetch Paper Details
- Implementation:Haosulab ManiSkill KitchenObjects
- Implementation:Predibase Lorax Flash Mixtral Modeling
- Implementation:Openai Openai python Response Failed Event
- Implementation:Haosulab ManiSkill GenerateTaskDocs
- Implementation:Evidentlyai Evidently Legacy Load Snapshots
- Implementation:OpenGVLab InternVL LLaVATrainer
- Implementation:Huggingface Diffusers Consolidated Test Report
Heuristics
- Heuristic:Eric mitchell Direct preference optimization RMSprop Over Adam
- Heuristic:Roboflow Rf detr Small Dataset Oversampling
- Heuristic:Datahub project Datahub Batch Size And Timeout Tuning
- Heuristic:ArroyoSystems Arroyo Stateful Operator TTL
- Heuristic:Princeton nlp Tree of thought llm Functools Partial Model Binding
- Heuristic:SqueezeAILab ETS Max Depth And Token Guards
- Heuristic:Volcengine Verl Sequence Length Balancing
- Heuristic:Kubeflow Pipelines Resource Sizing For Components
- Heuristic:Intel Ipex llm NF4 Quantization Best Practice
- Heuristic:ARISE Initiative Robosuite Numba BSOD Workaround
Environments
- Environment:Pyro ppl Pyro Python PyTorch Core
- Environment:ArroyoSystems Arroyo Python UDF Runtime
- Environment:Allenai Open instruct vLLM Inference
- Environment:Spcl Graph of thoughts Local LLaMA GPU Inference
- Environment:Truera Trulens Python Core Environment
- Environment:Recommenders team Recommenders Spark Environment
- Environment:Snorkel team Snorkel SpaCy NLP
- Environment:Shiyu coder Kronos DDP Multi GPU Environment
- Environment:BerriAI Litellm Redis Cache Backend
- Environment:Apache Beam Java Build Environment