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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:Truera Trulens Snowflake Observability Pipeline
- Workflow:Apache Flink Hybrid Source Switching
- Workflow:Online ml River Online Clustering
- Workflow:ContextualAI HALOs Reward Model Training
- Workflow:Mistralai Client python Finetuning Job Management
- Workflow:ARISE Initiative Robosuite Human Demonstration Collection
- Workflow:ArroyoSystems Arroyo UDF Development
- Workflow:Langgenius Dify RAG Pipeline Development
- Workflow:Shiyu coder Kronos Batch Prediction
- Workflow:Huggingface Diffusers LoRA Finetuning
Principles
- Principle:DataTalksClub Data engineering zoomcamp Streaming Data Model
- Principle:Elevenlabs Elevenlabs python TTS Model Configuration
- Principle:Recommenders team Recommenders SAR Algorithm
- Principle:Interpretml Interpret Explanation Preservation
- Principle:Tencent Ncnn TorchScript Export
- Principle:InternLM Lmdeploy Image Loading
- Principle:Huggingface Trl SFT Model Saving
- Principle:Explodinggradients Ragas Optimization Loss Functions
- Principle:Tensorflow Serving Multi Model Batching
- Principle:Webdriverio Webdriverio Selector Optimization
Implementations
- Implementation:Haifengl Smile SVD EVD Results
- Implementation:Online ml River Datasets MovieLens100K
- Implementation:Openai Whisper Log Mel Spectrogram
- Implementation:NVIDIA TransformerEngine PyTorch Ext Comm Overlap
- Implementation:PacktPublishing LLM Engineers Handbook NoSQLBaseDocument Save
- Implementation:SeleniumHQ Selenium Point
- Implementation:Mlc ai Mlc llm JSON Parser
- Implementation:Microsoft Playwright Public Protocol Types
- Implementation:Hiyouga LLaMA Factory V1 Arg Utils
- Implementation:Openai Evals Classify Function
Heuristics
- Heuristic:Microsoft Agent framework Declaration Only Tools Pattern
- Heuristic:LLMBook zh LLMBook zh github io Reward Model LM Regularization
- Heuristic:Fastai Fastbook Embedding Size Rule
- Heuristic:OpenBMB UltraFeedback Principle Distribution Tuning
- Heuristic:Apache Shardingsphere DDL Refresher Superclass Fallback
- Heuristic:Intel Ipex llm DeepSpeed Tensor Parallel Tips
- Heuristic:Kubeflow Pipelines Resource Sizing For Components
- Heuristic:Mistralai Client python Stream File Uploads
- Heuristic:Mage ai Mage ai HTTP Error Classification
- Heuristic:AnswerDotAI RAGatouille Searcher Configuration By Collection Size
Environments
- Environment:Puppeteer Puppeteer Configuration Environment Variables
- Environment:Huggingface Transformers Python 310 Runtime
- Environment:PacktPublishing LLM Engineers Handbook Docker MongoDB Qdrant Infrastructure
- Environment:Onnx Onnx Cpp Build Environment
- Environment:Huggingface Diffusers Quantization Environment
- Environment:Ray project Ray Java Build Environment
- Environment:Kserve Kserve SRIOV RDMA Network
- Environment:Snorkel team Snorkel Dask Distributed
- Environment:Mlc ai Mlc llm WebGPU Browser Environment
- Environment:Recommenders team Recommenders Spark Environment