MLflow - Platform for Complete Machine Learning Lifecycle
Offered By: Devoxx via YouTube
Course Description
Overview
Discover how the MLflow open source platform streamlines the machine learning development lifecycle in this 31-minute Devoxx conference talk. Learn to track experiment runs and results across frameworks, register projects for easy reproducibility, and efficiently productionize models using Docker containers, Azure ML, or Amazon SageMaker. Gain insights from Quentin Ambard, a Solutions Architect at Databricks, as he shares his experience from French startups and explains how MLflow addresses the complexities of ML development beyond traditional software lifecycles. Explore techniques for trying multiple algorithms, tools, and parameters while ensuring reproducibility, especially crucial for deploying models in production environments.
Syllabus
MLflow: Platform for Complete Machine Learning Lifecycle by Quentin Ambard
Taught by
Devoxx
Related Courses
Create and Publish Pipelines for Batch Inferencing with AzurePluralsight Azure AI Fundamentals (AI-900) Cert Prep: 2 Principles of Machine Learning on Azure
LinkedIn Learning Understanding the Machine Learning Process and Embedding Models into Apps
Microsoft via YouTube VS Code, Azure ML, and GitHub Codespaces
Visual Studio Code via YouTube DP-100 Azure Machine Learning in Python-Basic to Advance
Udemy