data-labeling
claudeData labeling: annotation guidelines, platforms, inter-annotator agreement, active learning, weak supervision, and label error detection.
1 skill · 1 command · 1 agent
Feature engineering: feature stores, transformations, selection, time-series features, leakage checks, and drift.
Plugin feature-engineering from marketplace libre-mlops in HermeticOrmus/LibreMLOps-Claude-Code. Commands read from the repo's manifest — 1 month ago.
feature-engineering-patternsFeature engineering patterns with code: Feast feature store setup, sklearn pipelines with ColumnTransformer, time-series features, K-fold target encoding that avoids leakage, SHAP-based selection, and PSI drift monitoring. Use when building or reviewing model features.
/feature-engineering:featuresBuild a feature transformation pipeline, register features in Feast or Hopsworks, generate retrieval code for training or serving, or check for leakage, skew, and drift.
feature-engineerUse this agent when designing features or a feature store (Feast, Tecton, Hopsworks): transformations, selection, time-series and embedding features, leakage checks, online and offline skew, and feature drift. It treats the feature store as the contract between data engineering and modeling.
Data labeling: annotation guidelines, platforms, inter-annotator agreement, active learning, weak supervision, and label error detection.
1 skill · 1 command · 1 agent
ML data pipelines: Apache Beam, Spark, dbt, orchestration, streaming features, validation, and backfills.
1 skill · 1 command · 1 agent
Data versioning: DVC, Delta Lake, lineage, dataset cards, and reproducible dataset splits.
1 skill · 1 command · 1 agent
Distributed training: DDP, FSDP, DeepSpeed ZeRO, model parallelism, mixed precision, and multi-node debugging.
1 skill · 1 command · 1 agent
Experiment tracking: MLflow, Weights & Biases, Neptune, ClearML, hyperparameter search, and run organization.
1 skill · 1 command · 1 agent
GPU optimization: profiling, memory management, torch.compile, Flash Attention, Triton kernels, and quantization.
1 skill · 1 command · 1 agent
Query Trackio projects, runs, and metrics using the `trackio` CLI. Use when the user needs to list projects/runs/metrics, get summaries, or retrieve metric values from local Trackio databases. Supports both human-readable and JSON output formats. Covers project discovery, run inspection, metric querying, and system metrics. Designed for LLM agents and automation scripts.
1 skill
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
26 skills · 4 commands · 3 agents · 1 MCP server
ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
2 skills · 1 command · 3 agents
Data engineering, ML, and AI specialists - data pipelines, machine learning, LLM architecture
Agents for data engineering, machine learning, and AI development
12 agents
Track and manage model versions
1 skill · 1 command
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