Model Tracking with MLflow in Azure Machine Learning

11 Sep 2025 03:30 AM CST

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Webinar Overview

Model Tracking with MLflow in Azure Machine Learning MLflow, integrated into Azure ML, helps track, organize, and reproduce machine learning experiments with ease. It captures metadata like parameters, metrics, and model versions, providing transparency and control across the model lifecycle. This part of the talk will demonstrate how to use MLflow for seamless model versioning and collaboration

Key Points

MLflow integration helps log parameters, metrics, and model artifacts in real time.
Facilitates reproducibility and version control of experiments.
Enhances collaboration with centralized tracking and easy comparisons across runs.

Meet The Trainer

Nidhi Karthik Nayak

A seasoned professional with over 10 years of experience in AI, Generative AI, and advanced data science training and development, specializing in Python, Machine Learning, NLP, and Azure services, with a history of impactful training sessions and innovative project achievements. Associated with Koenig since June 2023.

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Model Tracking with MLflow in Azure Machine Learning

Webinar Summary:

Model Tracking with MLflow in Azure Machine Learning MLflow, integrated into Azure ML, helps track, organize, and reproduce machine learning experiments with ease. It captures metadata like parameters, metrics, and model versions, providing transparency and control across the model lifecycle. This part of the talk will demonstrate how to use MLflow for seamless model versioning and collaboration

11 Sep 2025 | 03:30 AM CST 2 Hours

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