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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:Datahub project Datahub Docker Quickstart Deployment
- Workflow:Microsoft Playwright Trace recording and debugging
- Workflow:Zai org CogVideo Diffusers Text to Video Inference
- Workflow:Rapidsai Cuml Time Series Forecasting
- Workflow:EvolvingLMMs Lab Lmms eval End to End Evaluation
- Workflow:Interpretml Interpret EBM Model Merging
- Workflow:Neuml Txtai RAG Pipeline
- Workflow:Apache Dolphinscheduler Workflow Failover Recovery
- Workflow:Openai Openai python Embeddings Generation
- Workflow:Pytorch Serve Model Deployment
Principles
- Principle:Mlflow Mlflow Training Execution
- Principle:Spcl Graph of thoughts Keyword Counting Prompt Design
- Principle:Ggml org Llama cpp Unicode Text Processing
- Principle:Microsoft LoRA LoRA Training Loop
- Principle:EvolvingLMMs Lab Lmms eval PassAtK Evaluation
- Principle:Apache Beam Element Bundling
- Principle:Langgenius Dify Documentation
- Principle:Lance format Lance Tag Management
- Principle:TobikoData Sqlmesh Forward Only Change Handling
- Principle:FMInference FlexLLMGen AIO Performance Benchmarking
Implementations
- Implementation:Roboflow Rf detr Supervision Annotators
- Implementation:Online ml River Anomaly PAD
- Implementation:Microsoft Agent framework AzureOpenAIResponsesClient Init
- Implementation:Interpretml Interpret PartitionMultiDimensionalTree
- Implementation:Microsoft Autogen Studio Agent Fields
- Implementation:Interpretml Interpret Gradient Histogram Bin
- Implementation:LaurentMazare Tch rs Tensor Iter
- Implementation:Online ml River Utils Norm
- Implementation:Teamcapybara Capybara Session Visit
- Implementation:Mage ai Mage ai Chargebee Common Invoices Schema
Heuristics
- Heuristic:Langfuse Langfuse LLM Rate Limit 24h Abandon
- Heuristic:TobikoData Sqlmesh Execution Time Caching
- Heuristic:Apache Airflow Scheduler Performance Tuning
- Heuristic:Langfuse Langfuse Eval Loop Prevention
- Heuristic:Helicone Helicone Provider URL Regex Priority
- Heuristic:Unslothai Unsloth VLLM Memory Utilization
- Heuristic:MarketSquare Robotframework browser MacOS Sonoma Startup Delay
- Heuristic:Fastai Fastbook Mixup Data Augmentation
- Heuristic:InternLM Lmdeploy KV Quantization Tradeoffs
- Heuristic:Sgl project Sglang Memory Fraction Tuning
Environments
- Environment:CARLA simulator Carla Python API Runtime
- Environment:NVIDIA NeMo Curator Video Codec Stack
- Environment:NVIDIA NeMo Curator RAPIDS GPU Stack
- Environment:Vibrantlabsai Ragas Python 3 9 Core Environment
- Environment:Marker Inc Korea AutoRAG GPU PyTorch Environment
- Environment:InternLM Lmdeploy CUDA GPU Runtime
- Environment:VainF Torch Pruning CUDA GPU Benchmarking
- Environment:Fede1024 Rust rdkafka Kafka Broker Runtime
- Environment:Run llama Llama index Python LlamaIndex Core
- Environment:Farama Foundation Gymnasium Python 3 10 Runtime