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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:Scikit learn contrib Imbalanced learn Ensemble Imbalanced Classification
- Workflow:AUTOMATIC1111 Stable diffusion webui Image postprocessing and upscaling
- Workflow:Pytorch Serve HuggingFace Transformer Serving
- Workflow:Tencent Ncnn Image Classification Inference
- Workflow:Huggingface Datatrove Dataset Tokenization
- Workflow:Spotify Luigi Database Ingestion Pipeline
- Workflow:ClickHouse ClickHouse Server Deployment
- Workflow:Cypress io Cypress E2E Test Execution
- Workflow:Zai org CogVideo Diffusers Image to Video Inference
- Workflow:PrefectHQ Prefect Per Worker Task Concurrency
Principles
- Principle:Online ml River Online Logistic Regression
- Principle:DistrictDataLabs Yellowbrick Color Palette Management
- Principle:ARISE Initiative Robosuite Robot Simulation Abstraction
- Principle:AUTOMATIC1111 Stable diffusion webui Postprocessing input selection
- Principle:Volcengine Verl Environment Setup
- Principle:Avhz RustQuant Stochastic Process Simulation
- Principle:LaurentMazare Tch rs Generative Adversarial Network
- Principle:Apache Dolphinscheduler Failover Process Initiation
- Principle:Mbzuai oryx Awesome LLM Post training Progressive Data Checkpointing
- Principle:Microsoft Autogen Swarm Execution
Implementations
- Implementation:Getgauge Taiko Focus
- Implementation:CrewAIInc CrewAI MongoDB Vector Search Tool
- Implementation:Explodinggradients Ragas ImageTextPrompt Class
- Implementation:CARLA simulator Carla RawData
- Implementation:DevExpress Testcafe Chrome Headless Config
- Implementation:Arize ai Phoenix Docs Site Config
- Implementation:Microsoft Autogen Agent State Models
- Implementation:Treeverse LakeFS S3 Path Convention
- Implementation:Google deepmind Mujoco Engine Collision GJK
- Implementation:Online ml River Bandit BayesUCB
Heuristics
- Heuristic:Bigscience workshop Petals Prompt Embeddings Float32 Precision
- Heuristic:Apache Spark K8s Container Patterns
- Heuristic:Romsto Speculative Decoding Seed Fixing For Reproducibility
- Heuristic:Shiyu coder Kronos Instance Normalization Clipping
- Heuristic:Apache Druid Explore Compare Query Strategy
- Heuristic:Zai org CogVideo Training Hyperparameter Defaults
- Heuristic:Sdv dev SDV Gaussian KDE Incompatibility
- Heuristic:Marker Inc Korea AutoRAG Passage Filter Safety Minimum
- Heuristic:Huggingface Alignment handbook Global Batch Size Scaling
- Heuristic:Marker Inc Korea AutoRAG Deterministic Evaluation Generation
Environments
- Environment:Tensorflow Serving Kubernetes Deployment Environment
- Environment:Googleapis Python genai Vertex AI Service Account
- Environment:Anthropics Anthropic sdk python AWS Bedrock Environment
- Environment:Mistralai Client python Azure Deployment Environment
- Environment:Evidentlyai Evidently LLM Evaluation Environment
- Environment:Norrrrrrr lyn WAInjectBench Conda Python 39 CUDA Environment
- Environment:Apache Airflow Development Contributor Environment
- Environment:PacktPublishing LLM Engineers Handbook Docker MongoDB Qdrant Infrastructure
- Environment:Intel Ipex llm Build Environment
- Environment:ChenghaoMou Text dedup Python 3 12 Environment