Essentials of MLOps with Azure: 3 Spark MLflow Projects on Databricks

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Noah Gift

18:09

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01 - Essentials of MLOps with Azure.mp4

00:26

02 - Explore the Databricks Azure interface.mp4

03:27

03 - Run MLflow projects on Databricks.mp4

06:15

04 - Databricks autologging.mp4

03:48

05 - Track model development.mp4

04:13

Description

This series of courses introduces you to the essentials of MLOps, the application of software engineering/devops principles to the development of machine learning applications. In this course, MLOps expert Noah Gift introduces you to several of the exciting things you can do with MLflow projects, using both Databricks and Azure. Noah explores the Databricks Azure interface, running MLflow projects, autologging, and tracking model development. He explains the differences between Data Science and Engineering mode and Machine Learning Mode, as well as and how each can be used most efficiently. Noah shows you the steps to do remote experiment tracking and training within the Databricks platform. He also walks you through Databricks autologging and track model development.

Note: This course was created by Noah Gift. We are pleased to host this training in our library.

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Apache Spark

Microsoft Azure

Noah Gift

Instructor's Courses

Author of Practical MLOps, Enterprise MLOps, Developing on AWS with C#, Pragmatic AI, and Python for DevOps. Certified on Multiple MLOps certifications including Google-Professional Machine Learning Engineer and AWS Certified Machine Learning - Specialty. Adjunct Professor at Duke MIDS & Northwestern Graduate Data Science & AI. Held business roles including CTO, general manager, consulting CTO, and cloud architect. Consults with start-ups and other companies on machine learning and cloud architecture. AWS ML Hero, Python Software Foundation Fellow, AWS Subject Matter on Machine Learning, AWS Certified Solutions Architect, AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, Google Certified Professional Architect, and AWS Academy Accredited Instructor. Published books, videos, and courses on cloud machine learning, DevOps, Python, Data Science, Big Data and AI. ★ Specialties ★ ° Cloud-native Machine Learning and AI ° Directly teaching cutting edge skills to students that lead to jobs ° Creating world-class content in all forms ° Building Companies ° Shipping new Products ° Leading and growing engineering teams ° Production Machine Learning, Deep Learning, Big Data, and AI ° Serverless Data Engineering ° Advising Early Stage Startups/Consulting CTO services ° Distributed Systems and Scalability

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