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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:PacktPublishing LLM Engineers Handbook RAG Inference
- Workflow:Princeton nlp SimPO SimPO Training
- Workflow:Deepset ai Haystack Document Preprocessing Pipeline
- Workflow:Microsoft DeepSpeedExamples RLHF Training Pipeline
- Workflow:Huggingface Alignment handbook SFT DPO Alignment Pipeline
- Workflow:SqueezeAILab ETS Answer Evaluation Pipeline
- Workflow:Google deepmind Dm control Composer Environment Building
- Workflow:Ray project Ray Cross Language Invocation
- Workflow:Eric mitchell Direct preference optimization Custom Dataset Integration
- Workflow:NVIDIA DALI Image Preprocessing Pipeline
Principles
- Principle:Langgenius Dify PromptEngineering
- Principle:Volcengine Verl Multi Turn Data Preparation
- Principle:Scikit learn Scikit learn Cross Decomposition
- Principle:Apache Flink Source Switching
- Principle:Huggingface Diffusers ControlNet Output Refinement
- Principle:Tencent Ncnn PNNX Model Conversion
- Principle:Microsoft Playwright Element Location and Interaction
- Principle:Datahub project Datahub Sample Data Loading
- Principle:Unstructured IO Unstructured Pipeline Output Validation
- Principle:Apache Beam Job Preparation
Implementations
- Implementation:Interpretml Interpret Cpu 64
- Implementation:Datajuicer Data juicer TagsSpecifiedFieldSelector
- Implementation:Vespa engine Vespa SystemInfo
- Implementation:NVIDIA NeMo Aligner Preprocess HelpSteer Data
- Implementation:Microsoft Playwright HappyEyeballs
- Implementation:Lakeraai Pint benchmark HuggingFaceModelEvaluation Evaluate
- Implementation:Huggingface Trl RewardTrainer Prepare Dataset
- Implementation:Microsoft Onnxruntime CPU ActivationsGrad
- Implementation:Scikit learn Scikit learn FastICA
- Implementation:Helicone Helicone UseColumnResize
Heuristics
- Heuristic:Fastai Fastbook Random Forest Defaults
- Heuristic:Neuml Txtai LLM Context Window Fallback
- Heuristic:Apache Druid Capability Detection Strategy
- Heuristic:Wandb Weave Batch Processing Tuning
- Heuristic:NVIDIA NeMo Curator Semantic Dedup Cluster Sizing
- Heuristic:Dotnet Machinelearning Sparsity Threshold Optimization
- Heuristic:Unstructured IO Unstructured Libmagic Filetype Accuracy
- Heuristic:OpenGVLab InternVL Packed Training Buffer Management
- Heuristic:SeldonIO Seldon core Model Load Timeout Tip
- Heuristic:LLMBook zh LLMBook zh github io Reward Model LM Regularization
Environments
- Environment:PacktPublishing LLM Engineers Handbook Python 3 11 Poetry Environment
- Environment:Microsoft Playwright Node Runtime Environment
- Environment:Openclaw Openclaw State Directory And Credentials
- Environment:Google deepmind Dm control EGL Headless Rendering
- Environment:Alibaba MNN ARM Mobile Environment
- Environment:Haotian liu LLaVA Python CUDA Training Environment
- Environment:MaterializeInc Materialize Buildkite CI Runtime
- Environment:Datahub project Datahub Docker Runtime
- Environment:Ggml org Ggml CUDA GPU Environment
- Environment:InternLM Lmdeploy Python Dependencies