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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:Apache Shardingsphere Dynamic Rule Configuration Change
- Workflow:Microsoft Playwright Network mocking and interception
- Workflow:Elevenlabs Elevenlabs python Realtime TTS Streaming
- Workflow:Dagster io Dagster Bluesky Analytics
- Workflow:Mbzuai oryx Awesome LLM Post training Awesome List Curation
- Workflow:Online ml River Time Series Forecasting
- Workflow:Diagram of thought Diagram of thought DoT Prompt Customization
- Workflow:Speechbrain Speechbrain Whisper ASR Finetuning
- Workflow:CARLA simulator Carla Traffic Generation
- Workflow:Openai Whisper Word Level Timestamps
Principles
- Principle:OpenGVLab InternVL Dynamic Resolution Preprocessing
- Principle:Unstructured IO Unstructured Memory Profiling
- Principle:Huggingface Peft Causal LM Dataset Preparation
- Principle:Ray project Ray Application Deployment
- Principle:Openai Whisper Sliding Window Decoding
- Principle:AUTOMATIC1111 Stable diffusion webui Environment Reproducibility
- Principle:DistrictDataLabs Yellowbrick Visualization Rendering
- Principle:Farama Foundation Gymnasium Reproducible Seeding
- Principle:Pyro ppl Pyro Prior Specification
- Principle:Ucbepic Docetl Chunk Processing
Implementations
- Implementation:Scikit learn contrib Imbalanced learn BalancedBaggingClassifier
- Implementation:Marker Inc Korea AutoRAG Raw And Corpus Init
- Implementation:Openai Openai python Response Output Text Param
- Implementation:Ollama Ollama Llama KV Cells
- Implementation:Treeverse LakeFS ImportStart
- Implementation:NVIDIA NeMo Aligner Load From NeMo
- Implementation:LMCache LMCache Observability
- Implementation:NVIDIA TransformerEngine GEMM Config
- Implementation:Ggml org Ggml Cpu sgemm
- Implementation:Facebookresearch Habitat lab Dataset Utils
Heuristics
- Heuristic:Sktime Pytorch forecasting Early Stopping Patience
- Heuristic:OpenRLHF OpenRLHF Off Policy IS Correction Tip
- Heuristic:Mlc ai Mlc llm Engine Mode Selection
- Heuristic:Groq Groq python Streaming Usage Stats
- Heuristic:Apache Beam Thread Pool Parallelism Sizing
- Heuristic:Elevenlabs Elevenlabs python VAD vs Manual Commit Strategy
- Heuristic:Princeton nlp SimPO Dropout Disabling
- Heuristic:Junyanz Pytorch CycleGAN and pix2pix CuDNN Benchmark Scale Width
- Heuristic:Triton inference server Server Server Default Configuration
- Heuristic:Langgenius Dify Env Sync Upgrade Strategy
Environments
- Environment:TobikoData Sqlmesh Snowflake Connection
- Environment:BerriAI Litellm Docker Deployment
- Environment:Triton inference server Server GPU CUDA Runtime
- Environment:Kserve Kserve Cert Manager
- Environment:Unstructured IO Unstructured Libmagic
- Environment:CarperAI Trlx Python Accelerate
- Environment:Treeverse LakeFS Spark GC Environment
- Environment:Marker Inc Korea AutoRAG VLLM Environment
- Environment:Lm sys FastChat LoRA QLoRA Training Environment
- Environment:Online ml River Python Runtime Environment