Pluralsight – Production Machine Learning Systems 2024-9

Production Machine Learning Systems course. This course teaches you how to implement different types of production machine learning systems. Among the trainings of this course, static, dynamic and continuous trainings, static and dynamic inference, and batch and online processing can be mentioned. You’ll cover TensorFlow’s abstraction levels, different options for distributed training, and how to write distributed training models with custom estimators. This is the second course in the series of advanced machine learning courses on Google Cloud. After completing this course, you can enroll in the Image Understanding with TensorFlow course on Google Cloud. In this course, you will get to know practically the challenges of implementing machine learning systems in the real world. Also, you will learn how to use various tools and techniques to improve the performance and scalability of your models.

What you will learn:

• Implementation of different types of production machine learning systems
• Static, dynamic and continuous training
• Static and dynamic inference
• Batch and online processing
• TensorFlow abstraction levels
• Different options for distributed learning
• How to write distributed training models with custom estimators

This course is suitable for people who:

• Looking to learn how to implement large-scale machine learning systems
• Want to learn the advanced levels of TensorFlow
• Looking to increase their skills in the field of machine learning
• They want to use Google Cloud to implement machine learning models

Production Machine Learning Systems course specifications

• Publisher: Pluralsight
• Instructor: Google Cloud
• Training level: beginner to advanced
• Training duration: 2 hours and 29 minutes

Course headings

Course images

Sample video of the course

download link

Download file – 357 MB

File(s) password: www.downloadly.ir

File size

357 MB