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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:Duckdb Duckdb Source Amalgamation And Packaging
- Workflow:Apache Kafka Broker Startup
- Workflow:Speechbrain Speechbrain CTC ASR Training
- Workflow:SeldonIO Seldon core Inference Pipeline
- Workflow:Openai Evals Implementing a custom completion function
- Workflow:Cleanlab Cleanlab Token Classification Label Quality
- Workflow:BerriAI Litellm Observability Integration
- Workflow:Langgenius Dify Plugin Installation and Configuration
- Workflow:ARISE Initiative Robosuite Environment Setup And Simulation
- Workflow:Haosulab ManiSkill Imitation Learning Pipeline
Principles
- Principle:Ggml org Llama cpp MemoryAbstraction
- Principle:Open compass VLMEvalKit Judge LLM Construction
- Principle:Openai Openai agents python Approval Processing
- Principle:Apache Paimon Lance Table Configuration
- Principle:Google deepmind Mujoco API Utilities
- Principle:Scikit learn Scikit learn Partial Dependence Analysis
- Principle:Google deepmind Dm control MJCF Physics Compilation
- Principle:OpenRLHF OpenRLHF Reward Model Training Loop
- Principle:Apache Kafka Broker Invocation
- Principle:Mage ai Mage ai Schema Validation
Implementations
- Implementation:Huggingface Alignment handbook Get Tokenizer
- Implementation:Promptfoo Promptfoo Table Renderer
- Implementation:LMCache LMCache Periodic Thread
- Implementation:Fastai Fastbook DataBlock
- Implementation:Online ml River Optim Nadam
- Implementation:Unslothai Unsloth GEMM Forward Kernel
- Implementation:Open compass VLMEvalKit WeMath Utils
- Implementation:Bentoml BentoML OCIBuilder Base
- Implementation:Tensorflow Tfjs Advanced Activations
- Implementation:Speechbrain Speechbrain Train RescueSpeech
Heuristics
- Heuristic:Huggingface Datasets Flatten Indices Performance
- Heuristic:Puppeteer Puppeteer Navigation Race Condition Avoidance
- Heuristic:LLMBook zh LLMBook zh github io Greedy Decoding Temperature Zero
- Heuristic:Getgauge Taiko Navigation Wait Strategy
- Heuristic:Snorkel team Snorkel Binary Only Slicing
- Heuristic:Fede1024 Rust rdkafka Producer Flush Before Drop
- Heuristic:Isaac sim IsaacGymEnvs Factory Velocity Limits
- Heuristic:OpenBMB UltraFeedback Position Bias Mitigation
- Heuristic:Ggml org Llama cpp Context Size Alignment
- Heuristic:Vespa engine Vespa KStemmer Dictionary Loading
Environments
- Environment:NVIDIA TransformerEngine GPU Compute Capability
- Environment:HKUDS AI Trader API Credentials
- Environment:Teamcapybara Capybara Selenium WebDriver Environment
- Environment:Deepspeedai DeepSpeed CUDA GPU Environment
- Environment:Hpcaitech ColossalAI ColossalChat Training Environment
- Environment:Predibase Lorax Python Server Dependencies
- Environment:Intel Ipex llm Build Environment
- Environment:DataExpert io Data engineer handbook Statsig API Environment
- Environment:Confident ai Deepeval LLM Provider Credentials
- Environment:Huggingface Optimum Python Core Dependencies