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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:Recommenders team Recommenders Neural Collaborative Filtering
- Workflow:Arize ai Phoenix Span Annotation Pipeline
- Workflow:BerriAI Litellm Response Caching
- Workflow:Langgenius Dify App Creation and Configuration
- Workflow:Getgauge Taiko Headless Browser Testing
- Workflow:Neuml Txtai Workflow Orchestration
- Workflow:InternLM Lmdeploy W4A16 AWQ Quantization
- Workflow:Kserve Kserve InferenceGraph Pipeline
- Workflow:Dotnet Machinelearning Binary Classification Pipeline
- Workflow:Togethercomputer Together python Embeddings And Reranking
Principles
- Principle:OpenGVLab InternVL Dynamic Resolution Preprocessing
- Principle:Huggingface Optimum Accelerated Pipeline Configuration
- Principle:Fastai Fastbook Learning Rate Selection
- Principle:Protectai Modelscan Scanner Plugin Architecture
- Principle:Huggingface Datasets Archive Extraction
- Principle:Apache Hudi Query Type Definition
- Principle:Eric mitchell Direct preference optimization DPO Loss
- Principle:Openai Openai node Parsed Output Consumption
- Principle:Huggingface Datasets Feature Schema Inspection
- Principle:ARISE Initiative Robosuite Controller Abstraction
Implementations
- Implementation:NVIDIA NeMo Aligner Custom Checkpoint Callback
- Implementation:Ucbepic Docetl FastDecomposer
- Implementation:Pyro ppl Pyro SubstituteMessenger
- Implementation:Marker Inc Korea AutoRAG Extract Best Config
- Implementation:Princeton nlp SimPO Get Tokenizer and Model Config
- Implementation:Huggingface Alignment handbook Trainer Save And Push
- Implementation:Microsoft DeepSpeedExamples PreLN Bert LayerDrop Modeling
- Implementation:DistrictDataLabs Yellowbrick RadViz Visualizer
- Implementation:Langfuse Langfuse StorageService UploadFile
- Implementation:Openai Whisper Load Model
Heuristics
- Heuristic:Obss Sahi Auto Slice Resolution
- Heuristic:Datahub project Datahub Docker Memory Preflight
- Heuristic:Deepspeedai DeepSpeed Sequence Parallel PyTorch Version
- Heuristic:Apache Airflow Scheduler Performance Tuning
- Heuristic:Kubeflow Pipelines Cache Staleness In Recursive Pipelines
- Heuristic:Openai Openai agents python Sensitive Data Logging Defaults
- Heuristic:ARISE Initiative Robomimic BatchNorm To GroupNorm For EMA
- Heuristic:ChenghaoMou Text dedup Bloom Filter Single Process
- Heuristic:Promptfoo Promptfoo Adaptive Concurrency Tuning
- Heuristic:Nautechsystems Nautilus trader Parquet Row Group Tuning
Environments
- Environment:Kubeflow Kubeflow Python KFP SDK Environment
- Environment:Trailofbits Fickling Python Runtime
- Environment:TA Lib Ta lib python Python Build Environment
- Environment:ClickHouse ClickHouse OpenSSL Runtime
- Environment:CARLA simulator Carla Build From Source Requirements
- Environment:Apache Shardingsphere Etcd Cluster Coordination
- Environment:Nautechsystems Nautilus trader Python Cython Rust Runtime
- Environment:Sgl project Sglang Kubernetes
- Environment:Vllm project Vllm AMD ROCm
- Environment:Kserve Kserve Leader Worker Set