Essentials of MLOps with Azure: 3 Spark MLflow Projects on Databricks
Essentials of MLOps with Azure: 3 Spark MLflow Projects on Databricks
Duration: 18m 9s | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 57 MB
Genre: eLearning | Language: English
Duration: 18m 9s | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 57 MB
Genre: eLearning | Language: English
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.
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