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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:Turboderp org Exllamav2 Interactive Chat
- Workflow:Microsoft DeepSpeedExamples CIFAR10 Getting Started
- Workflow:Bentoml BentoML Multi Model Composition
- Workflow:Neuml Txtai Semantic Search Pipeline
- Workflow:Isaac sim IsaacGymEnvs Policy Inference and Evaluation
- Workflow:Facebookresearch Habitat lab PointNav PPO Training
- Workflow:Mlc ai Web llm Text Embeddings And RAG
- Workflow:Vespa engine Vespa Config subscription lifecycle
- Workflow:Tensorflow Serving Kubernetes Deployment
- Workflow:Kserve Kserve LLM Disaggregated Serving
Principles
- Principle:Interpretml Interpret Feature Group Importance
- Principle:Openai Whisper Output Formatting
- Principle:Mlflow Mlflow Model Version Management
- Principle:Openai Evals Eval Progress Tracking
- Principle:Lm sys FastChat LoRA Adapter Injection
- Principle:Apache Kafka Process Launch
- Principle:Microsoft Onnxruntime TensorBoard Monitoring
- Principle:Speechbrain Speechbrain LibriTTS Data Preparation
- Principle:Avhz RustQuant Day Count Conventions
- Principle:Sdv dev SDV Constraint Integration
Implementations
- Implementation:Microsoft Playwright ArtifactDispatcher
- Implementation:Infiniflow Ragflow Custom Exceptions
- Implementation:Openai Openai node FinalChatCompletion
- Implementation:Pytorch Serve Llama2 Tokenizer
- Implementation:Sktime Pytorch forecasting EnEmbedding
- Implementation:Haosulab ManiSkill ShaderConfig
- Implementation:Alibaba MNN LLM Config JSON
- Implementation:Scikit learn contrib Imbalanced learn NearMiss
- Implementation:Cohere ai Cohere python V2Client Rerank
- Implementation:Hiyouga LLaMA Factory DPO Trainer
Heuristics
- Heuristic:Junyanz Pytorch CycleGAN and pix2pix Adam Beta1 Half
- Heuristic:Fastai Fastbook Embedding Size Rule
- Heuristic:Webdriverio Webdriverio Default Timeout Configuration
- Heuristic:Duckdb Duckdb Test Development Guidelines
- Heuristic:PrefectHQ Prefect HTTP Connection Pool Tuning
- Heuristic:Danijar Dreamerv3 XLA GPU Optimization Flags
- Heuristic:Groq Groq python Retry Backoff Strategy
- Heuristic:Axolotl ai cloud Axolotl Gradient Checkpointing Reentrant Rules
- Heuristic:Intel Ipex llm LoRA Target All Linear Layers
- Heuristic:Intel Ipex llm Use Cache Training Vs Inference
Environments
- Environment:Nautechsystems Nautilus trader Asyncio Uvloop Event Loop
- Environment:Lance format Lance Rust Toolchain
- Environment:ARISE Initiative Robomimic HuggingFace Hub Dependencies
- Environment:Cleanlab Cleanlab Image Quality Dependencies
- Environment:Run llama Llama index Fsspec Remote Storage
- Environment:Hiyouga LLaMA Factory Distributed Training Environment
- Environment:Microsoft LoRA NLG Eval External Tools
- Environment:Cypress io Cypress Node Runtime Environment
- Environment:Kubeflow Pipelines KFP Backend Deployment
- Environment:Snorkel team Snorkel PySpark