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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:Apache Hudi Flink Streaming Write
- Workflow:Openai Openai node Fine Tuning
- Workflow:Confident ai Deepeval Synthetic Dataset Generation
- Workflow:Trailofbits Fickling Pickle Decompilation and Tracing
- Workflow:DistrictDataLabs Yellowbrick Cluster Analysis
- Workflow:Intel Ipex llm DPO Finetuning
- Workflow:Volcengine Verl Supervised Fine Tuning
- Workflow:Eric mitchell Direct preference optimization DPO Preference Training
- Workflow:DataExpert io Data engineer handbook AB Experimentation Server
- Workflow:Openai Evals Running a single eval
Principles
- Principle:InternLM Lmdeploy Image Loading
- Principle:Zai org CogVideo SAT Prompt Input
- Principle:Gretelai Gretel synthetics Conditional Data Sampling
- Principle:Arize ai Phoenix Prompt Creation
- Principle:Explodinggradients Ragas Results Analysis
- Principle:Apache Hudi Clustering Layout Analysis
- Principle:Cleanlab Cleanlab Token Label Issue Filtering
- Principle:Openai Openai node Fine Tuning Job Creation
- Principle:Togethercomputer Together python Dataset Preparation
- Principle:Huggingface Datasets CSV Import
Implementations
- Implementation:Haotian liu LLaVA CLI Main
- Implementation:Openai Openai python Eval Create Params
- Implementation:Alibaba ROLL MegatronTrainStrategy Train Step
- Implementation:Getgauge Taiko Element Base
- Implementation:CarperAI Trlx NeMo SFT Model
- Implementation:Hiyouga LLaMA Factory Model Args
- Implementation:Tensorflow Serving Bundle Factory Util
- Implementation:FlagOpen FlagEmbedding LLM Embedder Eval QReCC
- Implementation:Langfuse Langfuse Seeder Orchestrator
- Implementation:Online ml River Datasets Base
Heuristics
- Heuristic:Shiyu coder Kronos Learning Rate And Optimizer Tuning
- Heuristic:Deepset ai Haystack BM25 Score Scaling
- Heuristic:Rapidsai Cuml GPU Cache Alignment
- Heuristic:Predibase Lorax Quantization Backend Selection
- Heuristic:Protectai Llm guard Token Limit Early Guard
- Heuristic:Astronomer Astronomer cosmos Static Parser Hang Workaround
- Heuristic:Eric mitchell Direct preference optimization Activation Checkpointing Memory
- Heuristic:BerriAI Litellm SSL Cipher Optimization
- Heuristic:Fede1024 Rust rdkafka Regular Polling Required
- Heuristic:FlowiseAI Flowise Heap Memory Configuration
Environments
- Environment:Dagster io Dagster GRPC Communication
- Environment:PacktPublishing LLM Engineers Handbook API Credentials
- Environment:Deepspeedai DeepSpeed Python Runtime Environment
- Environment:Deepset ai Haystack GPU Device Environment
- Environment:Kubeflow Kubeflow Python KFP SDK Environment
- Environment:Turboderp org Exllamav2 Build Toolchain
- Environment:Dotnet Machinelearning Platform Architecture Support
- Environment:ARISE Initiative Robosuite MuJoCo Python
- Environment:Langgenius Dify Docker Deployment Environment
- Environment:Sgl project Sglang Multi Platform Accelerators