Production Machine Learning Systems
Offered By: Pluralsight
Course Description
Overview
This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing.
This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.
This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.
Taught by
Google Cloud
Related Courses
Google Cloud Fundamentals: Core InfrastructureGoogle via Coursera Google Cloud Big Data and Machine Learning Fundamentals
Google Cloud via Coursera Serverless Data Analysis with Google BigQuery and Cloud Dataflow en Français
Google Cloud via Coursera Essential Google Cloud Infrastructure: Foundation
Google Cloud via Coursera Elastic Google Cloud Infrastructure: Scaling and Automation
Google Cloud via Coursera