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 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.
Taught by
Google Cloud
Related Courses
4.0 Shades of Digitalisation for the Chemical and Process IndustriesUniversity of Padova via FutureLearn A Day in the Life of a Data Engineer
Amazon Web Services via AWS Skill Builder FinTech for Finance and Business Leaders
ACCA via edX Accounting Data Analytics
University of Illinois at Urbana-Champaign via Coursera Accounting Data Analytics
Coursera