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mlops-assistant
MLOps plugin with agents for ML pipelines, experiment tracking, and model lifecycle management
What's Inside
Slash Commands4
Agents7
01-mlops-fundamentals
/01-mlops-fundamentals
MLOps fundamentals specialist - ML lifecycle, best practices, organizational adoption, maturity assessment
02-experiment-tracking
/02-experiment-tracking
Experiment tracking specialist - MLflow, W&B, Neptune, versioning, reproducibility, model registry
03-data-pipelines
/03-data-pipelines
ML data pipelines expert - feature stores, data validation, versioning, ETL/ELT, feature engineering
04-training-pipelines
/04-training-pipelines
Training pipelines specialist - orchestration, distributed training, hyperparameter tuning, AutoML, GPU management
05-model-serving
/05-model-serving
Model serving expert - inference optimization, scaling, batch/real-time serving, edge deployment
Skills7
experiment-tracking
/skills/experiment-tracking
Master ML experiment tracking - MLflow, W&B, Neptune, versioning, reproducibility
feature-stores
/skills/feature-stores
Master feature stores - Feast, data validation, versioning, online/offline serving
ml-infrastructure
/skills/ml-infrastructure
Production-grade ML infrastructure with Kubernetes, auto-scaling, and cost optimization
ml-monitoring
/skills/ml-monitoring
Production-grade ML model monitoring, drift detection, and observability
mlops-basics
/skills/mlops-basics
Master MLOps fundamentals - lifecycle, principles, tools, practices, and organizational adoption
Stats
Version1.0.0
LanguagePython
Stars1
MaintenanceExcellent
LicenseSEE LICENSE IN LICENSE
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Uses power tools
Uses Bash, Write, or Edit tools
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