Practical Deployment

Experiment Tracking

Recording hyperparameters, metrics, and artifacts from training runs for comparison and reproducibility.

This concept is essential for understanding practical deployment and forms a key part of modern AI systems.

  • MLOps
  • Training
  • Reproducibility

Tags

practical-deployment mlops training reproducibility

Related Terms

MLOps

Practices for deploying, monitoring, and maintaining machine learning models in production, combining ML and DevOps principles.

Training

The process of teaching a machine learning model by adjusting its parameters based on data to minimize prediction errors.

Added: November 18, 2025

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