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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:Marker Inc Korea AutoRAG Data Creation Pipeline
- Workflow:Lance format Lance Version Management
- Workflow:Microsoft LoRA LoRA Integration
- Workflow:Apache Beam Portable Pipeline Submission
- Workflow:Run llama Llama index ReAct Agent
- Workflow:CARLA simulator Carla Simulation Setup and First Steps
- Workflow:Teamcapybara Capybara RSpec Integration Setup
- Workflow:Astronomer Astronomer cosmos Kubernetes dbt execution
- Workflow:Cohere ai Cohere python Model Finetuning
- Workflow:Run llama Llama index RAG Query Pipeline
Principles
- Principle:AUTOMATIC1111 Stable diffusion webui LDSR Upscaler
- Principle:Neuml Txtai Voice Capture
- Principle:Infiniflow Ragflow Application Embedding
- Principle:Deepset ai Haystack Query Text Embedding
- Principle:Apache Hudi Result Delivery
- Principle:Tencent Ncnn Top K Classification
- Principle:Arize ai Phoenix Experiment Result Analysis
- Principle:Tensorflow Serving Version Policy Configuration
- Principle:Fastai Fastbook Classifier Data Preparation
- Principle:Ggml org Llama cpp Quantization
Implementations
- Implementation:Sgl project Sglang Program State Fork Join
- Implementation:Roboflow Rf detr Supervision Annotators
- Implementation:Kubeflow Pipelines XGBoost Train Incremental
- Implementation:Guardrails ai Guardrails Validator Tracing
- Implementation:SeleniumHQ Selenium Closure UI SubMenu
- Implementation:Rapidsai Cuml MBSGDClassifier
- Implementation:Openclaw Openclaw FlyToml RenderYaml
- Implementation:Farama Foundation Gymnasium HalfCheetahEnv V5
- Implementation:Google deepmind Mujoco Render GL2
- Implementation:Ray project Ray Serve DeploymentInfo
Heuristics
- Heuristic:Confident ai Deepeval Timeout and Retry Tuning
- Heuristic:Tensorflow Serving GPU Memory And CPU Optimization
- Heuristic:Facebookresearch Audiocraft Generation Parameter Defaults
- Heuristic:Rapidsai Cuml Quantile Split Differences
- Heuristic:Ollama Ollama Download Retry Strategy
- Heuristic:LLMBook zh LLMBook zh github io DPO Beta Hyperparameter
- Heuristic:Tencent Ncnn Lightmode Memory Optimization
- Heuristic:PrefectHQ Prefect Task Timeout Thread Limitation
- Heuristic:FMInference FlexLLMGen Pin Memory Tradeoffs
- Heuristic:Interpretml Interpret EBM Hyperparameter Tuning Guide
Environments
- Environment:Huggingface Open r1 Slurm Cluster
- Environment:Bentoml BentoML Triton Inference Server
- Environment:Alibaba ROLL Ascend NPU Environment
- Environment:Ucbepic Docetl LLM API Keys
- Environment:Unstructured IO Unstructured Libmagic
- Environment:Dagster io Dagster GRPC Communication
- Environment:Apache Kafka Committer Tools Environment
- Environment:Pola rs Polars Cloud Storage Environment
- Environment:Pyro ppl Pyro Distributed Training
- Environment:Trailofbits Fickling PyTorch