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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:Langchain ai Langchain Chat Model Invocation
- Workflow:Shiyu coder Kronos Qlib Finetuning
- Workflow:Dagster io Dagster ETL Pipeline
- Workflow:Huggingface Open r1 GRPO Reasoning Training
- Workflow:Facebookresearch Audiocraft JASCO Conditioned Music Generation
- Workflow:Datahub project Datahub Protobuf Schema Ingestion
- Workflow:Ray project Ray Serve Deployment
- Workflow:Spcl Graph of thoughts Custom GoT Use Case Integration
- Workflow:DistrictDataLabs Yellowbrick Model Selection and Tuning
- Workflow:Neuml Txtai API Deployment
Principles
- Principle:Datahub project Datahub Entity Read Modify
- Principle:Eventual Inc Daft Descriptive Statistics
- Principle:Online ml River Streaming Signal Processing
- Principle:Allenai Open instruct Beaker Experiment Launch
- Principle:Interpretml Interpret SHAP Tree Explanation
- Principle:Openai Openai python Embedding Input Preparation
- Principle:Neuml Txtai ONNX Export
- Principle:Microsoft Agent framework Approval Request Presentation
- Principle:Pyro ppl Pyro Deep Kernel Learning
- Principle:DistrictDataLabs Yellowbrick Dataset Loading
Implementations
- Implementation:Microsoft Onnxruntime SequenceInfo
- Implementation:Apache Shardingsphere JDBCRepository Persist
- Implementation:Microsoft DeepSpeedExamples BingBertSquad Training Utils
- Implementation:SeldonIO Seldon core Seldon Model Infer With Headers
- Implementation:Unslothai Unsloth SyntheticDataKit
- Implementation:OpenRLHF OpenRLHF ProcessRewardModelTrainer
- Implementation:Infiniflow Ragflow KnowledgeChunk Component
- Implementation:DataTalksClub Data engineering zoomcamp JsonConsumer Implementation
- Implementation:Ggml org Llama cpp Jinja Caps Header
- Implementation:Huggingface Optimum ExporterConfig Generate Dummy Inputs
Heuristics
- Heuristic:Pytorch Serve CPU Performance Tuning
- Heuristic:Openai Openai python Streaming Resource Management
- Heuristic:Apache Hudi Compaction Scheduling Safety
- Heuristic:Sktime Pytorch forecasting Encoder Decoder Length Limits
- Heuristic:Princeton nlp SimPO Left Truncation Strategy
- Heuristic:Langgenius Dify Extension Initialization Order
- Heuristic:Farama Foundation Gymnasium Action Space Normalization Tip
- Heuristic:ARISE Initiative Robomimic Data Worker Tuning By Modality
- Heuristic:Run llama Llama index Embedding Batch Size Tuning
- Heuristic:Rapidsai Cuml CUDA Kernel Caching
Environments
- Environment:Spotify Luigi SQLAlchemy Database
- Environment:Nightwatchjs Nightwatch BrowserStack Cloud
- Environment:SeldonIO Seldon core Kubernetes Cluster Environment
- Environment:Vllm project Vllm Buildkite
- Environment:Mbzuai oryx Awesome LLM Post training Python Pandas
- Environment:Haosulab ManiSkill Python SAPIEN Core
- Environment:TobikoData Sqlmesh GitHub CICD Runner
- Environment:Facebookresearch Audiocraft FAD TensorFlow Environment
- Environment:Deepspeedai DeepSpeed Multi Accelerator Environment
- Environment:Apache Kafka JVM Runtime Environment