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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:Mlfoundations Open flamingo Few Shot Evaluation
- Workflow:Facebookresearch Audiocraft EnCodec Compression Training
- Workflow:Huggingface Open r1 Dataset Pass Rate Filtering
- Workflow:Tensorflow Serving Batched Inference Pipeline
- Workflow:Apache Beam Local Pipeline Execution
- Workflow:Norrrrrrr lyn WAInjectBench Image Prompt Injection Detection
- Workflow:MarketSquare Robotframework browser Plugin Development
- Workflow:Scikit learn Scikit learn Hyperparameter Tuning
- Workflow:Deepset ai Haystack Document Indexing Pipeline
- Workflow:PeterL1n BackgroundMattingV2 Model export
Principles
- Principle:Unslothai Unsloth MoE Kernel Autotuning
- Principle:OpenRLHF OpenRLHF Optimizer and Scheduler Setup
- Principle:Microsoft Semantic kernel Orchestration Result Collection
- Principle:EvolvingLMMs Lab Lmms eval LLM as Judge
- Principle:Huggingface Datatrove Japanese Word Tokenization
- Principle:Apache Shardingsphere Versioned Change Persistence
- Principle:SeldonIO Seldon core Monitoring Pipeline Definition
- Principle:Apache Beam Pipeline Graph Construction
- Principle:Triton inference server Server Model Lifecycle Testing
- Principle:LMCache LMCache P2P Configuration
Implementations
- Implementation:Ollama Ollama Convert Glm4MoeLite
- Implementation:Huggingface Peft LoraConfig
- Implementation:Kornia Kornia AEPE Metric
- Implementation:CARLA simulator Carla Show Recorder File Info Tool
- Implementation:Microsoft Semantic kernel MistralAI Embeddings TestData
- Implementation:Apache Kafka Kafka Run Class Classpath
- Implementation:ARISE Initiative Robomimic FileUtils policy from checkpoint
- Implementation:Avhz RustQuant LogOption
- Implementation:Mit han lab Llm awq StreamGenerator
- Implementation:Confident ai Deepeval ConfidentInstrumentationSettings
Heuristics
- Heuristic:Vespa engine Vespa Log Level Inheritance Polling
- Heuristic:Explodinggradients Ragas Embedding Batch Size Tuning
- Heuristic:ChenghaoMou Text dedup False Positive Verification Tradeoff
- Heuristic:Hiyouga LLaMA Factory CUDA Memory Optimization
- Heuristic:Openai Whisper Temperature Fallback Strategy
- Heuristic:Mage ai Mage ai Sorted Data Bookmark Strategy
- Heuristic:Shiyu coder Kronos Instance Normalization Clipping
- Heuristic:Pyro ppl Pyro Enumeration Plate Nesting
- Heuristic:Microsoft Agent framework PowerFx Python Version Limit
- Heuristic:CarperAI Trlx KL Coefficient Adaptation
Environments
- Environment:Predibase Lorax CUDA GPU Runtime
- Environment:MarketSquare Robotframework browser Docker Container
- Environment:BerriAI Litellm Redis Cache Backend
- Environment:Tensorflow Serving Kubernetes Deployment Environment
- Environment:Ggml org Ggml CUDA GPU Environment
- Environment:Deepspeedai DeepSpeed XPU Environment
- Environment:Eric mitchell Direct preference optimization Python Dependencies
- Environment:Elevenlabs Elevenlabs python Python Websockets
- Environment:Pola rs Polars Rust Build Environment
- Environment:Tensorflow Tfjs Node Native Runtime