Recommendation Systems with TensorFlow on Google Cloud faq

learnersLearners:
instructor Instructor: Google Cloud instructor-icon
duration Duration: 7.00 instructor-icon

In this course, learners will use TensorFlow and Google Cloud to build a recommendation system. Through the use of classification models and embeddings, learners will create a machine learning pipeline to create a powerful recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.

Course Feature Course Overview Course Provider
Go to class

Course Feature

costCost:

Free Trial

providerProvider:

Pluralsight

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

On-Demand

Course Overview

❗The content presented here is sourced directly from Pluralsight platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [February 21st, 2023]

What does this course tell?
(Please note that the following overview content is from the original platform)

In this course, you'll apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.
In this course, you'll apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.

We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
By taking this course, learners will acquire the skills and knowledge necessary to build a ML pipeline that functions as a recommendation engine. Specifically, learners will gain an understanding of classification models, embeddings, and ML pipelines, as well as how to use TensorFlow and Google Cloud to build a recommendation system. Additionally, learners will gain an understanding of how to deploy and monitor a recommendation system.

How does this course contribute to professional growth?
This course is part of the Advanced Machine Learning on Google Cloud series, which provides a comprehensive overview of the Google Cloud platform and its capabilities.

Is this course suitable for preparing further education?
This course is suitable for preparing further education in the field of machine learning and recommendation systems. It provides a comprehensive overview of the concepts and techniques used to build a ML pipeline that functions as a recommendation engine. The course also covers the use of classification models and embeddings, which are essential for further study in the field.

Course Provider

Provider Pluralsight's Stats at OeClass