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
Creative Applications of Deep Learning with TensorFlowKadenze Creative Applications of Deep Learning with TensorFlow III
Kadenze Creative Applications of Deep Learning with TensorFlow II
Kadenze 6.S191: Introduction to Deep Learning
Massachusetts Institute of Technology via Independent Learn TensorFlow and deep learning, without a Ph.D.
Google via Independent