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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:SeleniumHQ Selenium Chrome DevTools Protocol Integration
- Workflow:Huggingface Optimum Accelerated Inference Pipeline
- Workflow:Openai CLIP Zero shot image classification
- Workflow:Openai Openai agents python Multi Agent Handoff
- Workflow:TobikoData Sqlmesh Incremental model development
- Workflow:Openai Openai node Realtime Conversation
- Workflow:Isaac sim IsaacGymEnvs RL Policy Training
- Workflow:Bitsandbytes foundation Bitsandbytes 8bit LLM Int8 Inference
- Workflow:Pola rs Polars Data IO and Format Conversion
- Workflow:Rapidsai Cuml Dimensionality Reduction
Principles
- Principle:ClickHouse ClickHouse Object Pooling
- Principle:Webdriverio Webdriverio Service Hook Lifecycle
- Principle:Protectai Llm guard Emotion Detection
- Principle:Infiniflow Ragflow Conversation Management
- Principle:ChenghaoMou Text dedup Cluster Visualization
- Principle:Haosulab ManiSkill Environment Testing
- Principle:FlagOpen FlagEmbedding Embedder Training Configuration
- Principle:Guardrails ai Guardrails Stream Invocation
- Principle:ClickHouse ClickHouse Fast Integer Formatting
- Principle:Sgl project Sglang Server Health Monitoring
Implementations
- Implementation:Microsoft Semantic kernel Bing Search TestData
- Implementation:Mlflow Mlflow Docusaurus Config
- Implementation:Fastai Fastbook Untar Data Text
- Implementation:FlagOpen FlagEmbedding BGE Coder Utils
- Implementation:FlagOpen FlagEmbedding LLARA Pretrain Data
- Implementation:TobikoData Sqlmesh CICD Deploy Production
- Implementation:Run llama Llama index MultiModalEmbedding
- Implementation:Googleapis Python genai Part From Text
- Implementation:Speechbrain Speechbrain Prepare GigaSpeech
- Implementation:Lance format Lance Java BasePath
Heuristics
- Heuristic:Dagster io Dagster Lazy Import Pattern
- Heuristic:Wandb Weave Sentinel Value Handling
- Heuristic:Spotify Luigi Dynamic Requirements Generator
- Heuristic:Sail sg LongSpec TF32 And FP16 Training
- Heuristic:NVIDIA NeMo Aligner PPO Critic Warmup Tip
- Heuristic:Bentoml BentoML Worker Count Strategy
- Heuristic:Alibaba MNN Warning Deprecated Winograd Codegen
- Heuristic:Apache Shardingsphere DDL Refresher Superclass Fallback
- Heuristic:Obss Sahi Warning Deprecated Legacy NMS
- Heuristic:Facebookresearch Audiocraft FSDP Distributed Training Tips
Environments
- Environment:Google deepmind Mujoco Python Bindings Environment
- Environment:Microsoft DeepSpeedExamples CIFAR10 Training Environment
- Environment:Datahub project Datahub Python Ingestion
- Environment:Guardrails ai Guardrails LLM Provider API Keys
- Environment:Guardrails ai Guardrails OpenTelemetry Tracing
- Environment:Huggingface Trl vLLM Generation Environment
- Environment:Dagster io Dagster PostgreSQL Storage
- Environment:Huggingface Diffusers PyTorch CUDA Runtime
- Environment:Treeverse LakeFS Go Runtime Environment
- Environment:Anthropics Anthropic sdk python GCP Vertex Environment