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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:Alibaba ROLL Reward Flow Diffusion Pipeline
- Workflow:Interpretml Interpret EBM Training And Prediction
- Workflow:ArroyoSystems Arroyo Checkpoint Recovery
- Workflow:Marker Inc Korea AutoRAG Evaluation Data Creation
- Workflow:Cypress io Cypress Local Development Environment
- Workflow:Microsoft BIPIA Attack Success Rate Evaluation
- Workflow:Ggml org Llama cpp Interactive Chat
- Workflow:FlowiseAI Flowise Agentflow V2 Creation
- Workflow:Deepspeedai DeepSpeed ZeRO Distributed Training
- Workflow:Langchain ai Langgraph ReAct Agent Creation
Principles
- Principle:Ray project Ray Application Deployment
- Principle:AUTOMATIC1111 Stable diffusion webui High resolution fix
- Principle:NVIDIA NeMo Aligner Hydra Training Configuration
- Principle:Microsoft BIPIA Prompt Construction With Defense
- Principle:Getgauge Taiko File Attachment
- Principle:Getgauge Taiko Network Emulation
- Principle:Facebookresearch Habitat lab HITL Application Configuration
- Principle:Facebookresearch Habitat lab Benchmark Configuration
- Principle:Langchain ai Langgraph UI Component Management
- Principle:Infiniflow Ragflow Parser Options Configuration
Implementations
- Implementation:Openai Openai node ChatKit Threads Resource
- Implementation:Cohere ai Cohere python ApiError
- Implementation:Mage ai Mage ai Commercetools Orders Schema
- Implementation:CARLA simulator Carla Map API Spec
- Implementation:FlowiseAI Flowise SafeHTML
- Implementation:Pola rs Polars Streaming Show Graph
- Implementation:Deepspeedai DeepSpeed Normalize Layer
- Implementation:Microsoft Playwright React CT Mount
- Implementation:Ggml org Llama cpp Conversion Utils
- Implementation:Vespa engine Vespa Docproc ABI Spec
Heuristics
- Heuristic:Bigscience workshop Petals Batch Splitting Threshold
- Heuristic:Unstructured IO Unstructured Libmagic Filetype Accuracy
- Heuristic:Apache Shardingsphere Worker ID Reservation Strategy
- Heuristic:CarperAI Trlx PEFT LoRA Integration
- Heuristic:Cohere ai Cohere python Pydantic V1 V2 Compatibility
- Heuristic:Sktime Pytorch forecasting Gradient Clipping Value
- Heuristic:Apache Kafka Coordinator Loading Commit Interval
- Heuristic:Puppeteer Puppeteer Navigation Race Condition Avoidance
- Heuristic:Webdriverio Webdriverio Exponential Backoff Retry
- Heuristic:PacktPublishing LLM Engineers Handbook LoRA Finetuning Parameters
Environments
- Environment:Marker Inc Korea AutoRAG Korean NLP Dependencies
- Environment:PacktPublishing LLM Engineers Handbook Unsloth Finetuning Environment
- Environment:Apache Druid Druid Cluster Api
- Environment:Microsoft Agent framework Core Package Dependencies
- Environment:Lm sys FastChat SFT Training Environment
- Environment:Onnx Onnx Python Runtime Environment
- Environment:Farama Foundation Gymnasium JAX Functional Backend
- Environment:Sail sg LongSpec Inference Environment
- Environment:NVIDIA NeMo Curator NVIDIA DALI
- Environment:Eric mitchell Direct preference optimization PyTorch CUDA