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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:Triton inference server Server Quickstart Model Deployment
- Workflow:Openai Evals Creating a model graded eval
- Workflow:PacktPublishing LLM Engineers Handbook LLM Finetuning
- Workflow:Duckdb Duckdb Source Amalgamation And Packaging
- Workflow:Openai Openai python Realtime Conversation
- Workflow:Openclaw Openclaw Agent Message Loop
- Workflow:Cleanlab Cleanlab Multiannotator Consensus
- Workflow:Farama Foundation Gymnasium Policy Gradient Training
- Workflow:Openai Openai python Embeddings Generation
- Workflow:Astronomer Astronomer cosmos Dbt docs generation
Principles
- Principle:Duckdb Duckdb Benchmark Discovery
- Principle:Facebookresearch Habitat lab Task Dataset Selection
- Principle:Danijar Dreamerv3 Distributed Logger Aggregation
- Principle:Huggingface Transformers Quantized Inference
- Principle:Heibaiying BigData Notes HBase Table Creation
- Principle:Vespa engine Vespa Subscription Registration
- Principle:Hiyouga LLaMA Factory Gradient Checkpointing Theory
- Principle:Cohere ai Cohere python AWS SigV4 Authentication
- Principle:Ggml org Ggml Vulkan GPU Computation
- Principle:Allenai Open instruct DPO Loss Dispatch
Implementations
- Implementation:Lance format Lance BackgroundIterator
- Implementation:Apache Airflow BaseExecutor Interface
- Implementation:Facebookresearch Habitat lab HumanoidPickPolicy
- Implementation:VainF Torch Pruning Serialization
- Implementation:FlowiseAI Flowise ArrayRenderer
- Implementation:Mlc ai Mlc llm Attach Softmax Temperature Pass
- Implementation:Datajuicer Data juicer RemoveSpecificCharsMapper
- Implementation:Fastai Fastbook RandomForestRegressor
- Implementation:Open compass VLMEvalKit MMHELIX
- Implementation:Apache Shardingsphere PreciseHintShadowValue DTO
Heuristics
- Heuristic:LLMBook zh LLMBook zh github io BF16 Mixed Precision Default
- Heuristic:ThreeSR Awesome Inference Time Scaling Empty Venue Default Tip
- Heuristic:Haosulab ManiSkill Physics Solver Tuning
- Heuristic:Datahub project Datahub Spark Databricks Coalescing
- Heuristic:Microsoft Onnxruntime Convergence Debugging Tips
- Heuristic:Truera Trulens Rate Limiting And Retry Strategy
- Heuristic:Allenai Open instruct GPU Memory Utilization
- Heuristic:Vespa engine Vespa Document Batch Processing Strategy
- Heuristic:HKUDS AI Trader Market Type Auto Detection
- Heuristic:Datahub project Datahub Warning Deprecated Spark Lineage Legacy
Environments
- Environment:NVIDIA NeMo Aligner PyTriton Serving Environment
- Environment:Infiniflow Ragflow Python Runtime
- Environment:Microsoft LoRA NLG Eval External Tools
- Environment:Vllm project Vllm AArch64 CPU
- Environment:Liu00222 Open Prompt Injection Python Dependencies
- Environment:Ray project Ray CI Build Matrix Environment
- Environment:FlowiseAI Flowise Database Environment
- Environment:Explodinggradients Ragas Google Drive Backend Environment
- Environment:Snorkel team Snorkel PySpark
- Environment:Cleanlab Cleanlab Python Core Environment