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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:Risingwavelabs Risingwave Sink Connector Pipeline
- Workflow:ARISE Initiative Robomimic Training Policy From Demonstrations
- Workflow:Sdv dev SDV Multi table synthesis
- Workflow:Apache Shardingsphere Cluster Mode Initialization
- Workflow:Speechbrain Speechbrain Speech Enhancement Training
- Workflow:Langchain ai Langchain Vector Store Operations
- Workflow:Confident ai Deepeval End to End LLM Evaluation
- Workflow:Apache Beam Portable Pipeline Submission
- Workflow:OpenBMB UltraFeedback Completion Generation
- Workflow:Vibrantlabsai Ragas Experiment Driven Development
Principles
- Principle:Tensorflow Serving Static Path Source
- Principle:Lucidrains X transformers Encoder Decoder Training
- Principle:Turboderp org Exllamav2 Quantization Sensitivity Measurement
- Principle:BerriAI Litellm Integration Selection
- Principle:Spotify Luigi Task Persistence History
- Principle:Ggml org Ggml Tensor Creation
- Principle:Mlfoundations Open flamingo Classification Evaluation
- Principle:Lance format Lance Compaction Planning
- Principle:Turboderp org Exllamav2 KV Cache Allocation
- Principle:Google deepmind Mujoco CPU Model Loading
Implementations
- Implementation:Lance format Lance Dataset Restore
- Implementation:Microsoft Onnxruntime CPU ActivationsGrad
- Implementation:Deepspeedai DeepSpeed Transformer CUDA
- Implementation:Online ml River Datasets MaliciousURL
- Implementation:FMInference FlexLLMGen HELM Metric Evaluate
- Implementation:Langchain ai Langchain ChatOpenAI Constructor
- Implementation:Microsoft DeepSpeedExamples Prompt Eval
- Implementation:LaurentMazare Tch rs Min GPT
- Implementation:Huggingface Peft GraloraModel
- Implementation:Kornia Kornia Coordinate Grid
Heuristics
- Heuristic:Unslothai Unsloth Merge Memory Management
- Heuristic:Eric mitchell Direct preference optimization FSDP Batch Size Per GPU
- Heuristic:Gretelai Gretel synthetics Gumbel Softmax NaN Retry
- Heuristic:Cypress io Cypress Timeout Tuning
- Heuristic:NVIDIA NeMo Aligner Adam State Offloading Tip
- Heuristic:Langchain ai Langgraph Stream Mode Selection
- Heuristic:Sail sg LongSpec NCCL Distributed Settings
- Heuristic:Apache Spark Hardware Provisioning Tips
- Heuristic:Isaac sim IsaacGymEnvs DR Setup Only Flag
- Heuristic:Fastai Fastbook Dropout Regularization
Environments
- Environment:Kserve Kserve Istio Service Mesh
- Environment:Volcengine Verl Python Core Dependencies
- Environment:Microsoft Autogen Studio Server Environment
- Environment:ARISE Initiative Robomimic Robosuite Simulation Backend
- Environment:Treeverse LakeFS Spark GC Environment
- Environment:Promptfoo Promptfoo Node Runtime
- Environment:Lance format Lance Cloud Storage Credentials
- Environment:Explodinggradients Ragas Python Runtime Environment
- Environment:Alibaba MNN GPU Metal Environment
- Environment:Farama Foundation Gymnasium JAX Functional Backend