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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:Togethercomputer Together python Fine Tuning
- Workflow:Astronomer Astronomer cosmos Watcher execution mode
- Workflow:SeleniumHQ Selenium Contributor Development Workflow
- Workflow:Onnx Onnx Version Conversion
- Workflow:Cohere ai Cohere python Semantic Search With Rerank
- Workflow:Apache Paimon Table Read Write
- Workflow:OpenGVLab InternVL LoRA Finetuning
- Workflow:Google deepmind Dm control Locomotion Task Setup
- Workflow:Pyro ppl Pyro MCMC Inference
- Workflow:Pyro ppl Pyro Discrete Enumeration
Principles
- Principle:Microsoft Onnxruntime Nodejs Inference Execution
- Principle:Cohere ai Cohere python Text Embedding
- Principle:Apache Dolphinscheduler Failover Process Initiation
- Principle:Kubeflow Kubeflow Register Model
- Principle:MarketSquare Robotframework browser JavaScript Module Authoring
- Principle:DistrictDataLabs Yellowbrick RadViz Visualization
- Principle:Eric mitchell Direct preference optimization Concatenated Forward Pass
- Principle:Tensorflow Serving Canary Deployment
- Principle:Vibrantlabsai Ragas LLM Configuration
- Principle:Tensorflow Serving Session Bundle Migration
Implementations
- Implementation:ClickHouse ClickHouse IPv4andIPv6
- Implementation:Sgl project Sglang SM100 MLA TMA WarpSpecialized
- Implementation:Online ml River Utils Math
- Implementation:Google deepmind Mujoco USD Layer Sink
- Implementation:SeleniumHQ Selenium Router And LocalDistributor
- Implementation:Ollama Ollama Imagegen Dispatch
- Implementation:Cohere ai Cohere python V2ChatResponse Model
- Implementation:Triton inference server Server TritonPythonModel BLS
- Implementation:Datahub project Datahub ProtobufMessage
- Implementation:DataTalksClub Data engineering zoomcamp Kestra Docker Compose Setup
Heuristics
- Heuristic:Apache Dolphinscheduler Epoll Vs NIO Selection
- Heuristic:PacktPublishing LLM Engineers Handbook DPO Training Configuration
- Heuristic:Deepspeedai DeepSpeed FP16 Convergence Tips
- Heuristic:Mbzuai oryx Awesome LLM Post training Depth Limit Recursion At 2
- Heuristic:VainF Torch Pruning Pruning Ratio vs Parameter Ratio
- Heuristic:Microsoft DeepSpeedExamples ZeRO Inference Throughput Tuning
- Heuristic:Bigscience workshop Petals Randomized Rebalancing Intervals
- Heuristic:Microsoft Onnxruntime Convergence Debugging Tips
- Heuristic:Farama Foundation Gymnasium Shared Memory Vector Env Optimization
- Heuristic:Fede1024 Rust rdkafka Regular Polling Required
Environments
- Environment:Webdriverio Webdriverio Node Runtime Environment
- Environment:Microsoft Onnxruntime Distributed Training Environment
- Environment:Intel Ipex llm XPU Serving Environment
- Environment:Dotnet Machinelearning Platform Architecture Support
- Environment:Speechbrain Speechbrain HuggingFace Transformers
- Environment:Openai Whisper FFmpeg
- Environment:Ray project Ray Java Build Environment
- Environment:Heibaiying BigData Notes Spark 2 4 Environment
- Environment:Huggingface Datasets PyTorch Integration
- Environment:Unstructured IO Unstructured Profiling Tools