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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:Trailofbits Fickling PyTorch Payload Injection
- Workflow:Axolotl ai cloud Axolotl Multimodal Vision Finetuning
- Workflow:ClickHouse ClickHouse Contributing Pull Request
- Workflow:Langgenius Dify Plugin Installation and Configuration
- Workflow:Speechbrain Speechbrain Text to Speech Training
- Workflow:LLMBook zh LLMBook zh github io Supervised Finetuning
- Workflow:Princeton nlp Tree of thought llm Adding new task
- Workflow:Openai CLIP Prompt engineered classification
- Workflow:Datahub project Datahub Protobuf Schema Ingestion
- Workflow:Helicone Helicone Cost Calculation Pipeline
Principles
- Principle:Apache Paimon Multi Batch Data Writing
- Principle:Run llama Llama index Batch Evaluation Setup
- Principle:NVIDIA NeMo Curator Quality Filtering and Classification
- Principle:Puppeteer Puppeteer Device Emulation
- Principle:Onnx Onnx Reference Evaluation Init
- Principle:PacktPublishing LLM Engineers Handbook SageMaker Training Orchestration
- Principle:Microsoft Playwright Execute and Analyze Agent Results
- Principle:Bentoml BentoML Async Execution Patterns
- Principle:OpenHands OpenHands Action Server Startup
- Principle:Bitsandbytes foundation Bitsandbytes Global INT8 Quantization
Implementations
- Implementation:Microsoft Playwright Client EventEmitter
- Implementation:Anthropics Anthropic sdk python MessageParam Accumulation
- Implementation:Pyro ppl Pyro SearchInference
- Implementation:Unstructured IO Unstructured PartitionStrategy
- Implementation:FlowiseAI Flowise DataGrid
- Implementation:Predibase Lorax Validation Schema Extraction
- Implementation:Mage ai Mage ai PowerBI Client
- Implementation:Open compass VLMEvalKit MMHelix Binario Eval
- Implementation:Openai Openai node StrictJsonSchema Transform
- Implementation:SeleniumHQ Selenium NetworkUtils
Heuristics
- Heuristic:ContextualAI HALOs Online Round Budgeting
- Heuristic:Mit han lab Llm awq Skip QK Projection Clipping
- Heuristic:Lucidrains X transformers Flash Attention Configuration
- Heuristic:Scikit learn Scikit learn Random State Management
- Heuristic:Bigscience workshop Petals Short Inference Pool Merging
- Heuristic:Heibaiying BigData Notes Spark Streaming Local Threads Tip
- Heuristic:Openai Openai python Warning Deprecated Eval Stored Completions
- Heuristic:Nautechsystems Nautilus trader Order Rate Limiting Configuration
- Heuristic:Sktime Pytorch forecasting Early Stopping Patience
- Heuristic:Promptfoo Promptfoo WAL Mode Network Filesystem
Environments
- Environment:OpenGVLab InternVL DeepSpeed
- Environment:Protectai Modelscan Python Core Runtime
- Environment:Google deepmind Dm control GLFW Desktop Rendering
- Environment:Sail sg LongSpec Inference Environment
- Environment:PrefectHQ Prefect Prefect Server Database
- Environment:Nightwatchjs Nightwatch Node 18 Runtime
- Environment:ArroyoSystems Arroyo PostgreSQL Database
- Environment:Cypress io Cypress Browser Requirements
- Environment:Sgl project Sglang Distributed
- Environment:Evidentlyai Evidently Node Frontend Environment