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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:Guardrails ai Guardrails Streaming Validation
- Workflow:Scikit learn contrib Imbalanced learn SMOTE Resampling Pipeline
- Workflow:Vibrantlabsai Ragas RAG Evaluation
- Workflow:Marker Inc Korea AutoRAG Evaluation Data Creation
- Workflow:Volcengine Verl Supervised Fine Tuning
- Workflow:Microsoft Playwright Browser automation CLI
- Workflow:Isaac sim IsaacGymEnvs Policy Inference and Evaluation
- Workflow:CrewAIInc CrewAI Knowledge RAG Pipeline
- Workflow:Triton inference server Server Quickstart Model Deployment
- Workflow:Ggml org Llama cpp Model Quantization
Principles
- Principle:LaurentMazare Tch rs Advantage Actor Critic
- Principle:Tensorflow Serving Performance Monitoring
- Principle:Triton inference server Server Model Namespacing Testing
- Principle:Apache Dolphinscheduler Task Reassignment
- Principle:Pytorch Serve Parallelism Strategy
- Principle:Kornia Kornia Image Stitching
- Principle:DistrictDataLabs Yellowbrick Residual Analysis
- Principle:Tencent Ncnn Vulkan Inference Configuration
- Principle:Mlc ai Web llm Structured Output Parsing
- Principle:Protectai Llm guard Vault State Management
Implementations
- Implementation:Apache Paimon SplitRead
- Implementation:Online ml River Tree Splitter NominalClassif
- Implementation:Teamcapybara Capybara Node Actions Selection
- Implementation:Avhz RustQuant Surface
- Implementation:Mit han lab Llm awq Get prompter
- Implementation:Langchain ai Langgraph NamedBarrierValue Channel
- Implementation:Ucbepic Docetl PrettyJSON
- Implementation:Arize ai Phoenix PrecisionRecallFScore
- Implementation:Langchain ai Langgraph Add Messages
- Implementation:Sktime Pytorch forecasting NHiTS
Heuristics
- Heuristic:Explodinggradients Ragas Failed Metrics Return NaN
- Heuristic:Helicone Helicone Rate Limiting Fail Open
- Heuristic:Gretelai Gretel synthetics Mixed Precision Training Tradeoff
- Heuristic:Facebookresearch Habitat lab VER Tuning Guidelines
- Heuristic:Princeton nlp Tree of thought llm Value Caching
- Heuristic:Avdvg InjectGuard Embedding Normalization Cosine Equivalence
- Heuristic:Microsoft LoRA Label Smoothing NLG
- Heuristic:NVIDIA NeMo Curator GPU Memory Resource Allocation
- Heuristic:Liu00222 Open Prompt Injection PPL Threshold Tuning
- Heuristic:Datahub project Datahub Batch Size And Timeout Tuning
Environments
- Environment:Marker Inc Korea AutoRAG GPU PyTorch Environment
- Environment:Intel Ipex llm NPU Environment
- Environment:Langchain ai Langchain Unit Test Network Isolation
- Environment:PrefectHQ Prefect AI Integration Credentials
- Environment:Turboderp org Exllamav2 Build Toolchain
- Environment:Arize ai Phoenix Python Runtime
- Environment:Bitsandbytes foundation Bitsandbytes XPU SYCL Runtime
- Environment:Kubeflow Kubeflow Python KFP SDK Environment
- Environment:Junyanz Pytorch CycleGAN and pix2pix Python PyTorch Runtime
- Environment:Huggingface Datasets Lance Dependencies