In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine.
Recommendation Systems on Google Cloud
About this Course
What you will learn
Devise a content-based recommendation engine.
Implement a collaborative filtering recommendation engine.
Build a hybrid recommendation engine with user and content embeddings.
Use reinforcement learning techniques for contextual bandits in the context of recommendations.
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Syllabus - What you will learn from this course
Welcome to Recommendation Systems on Google Cloud
This module previews the topics covered in the course.
Recommendation Systems Overview
This module defines what recommendation systems are, reviews the different types of recommendation systems, and discusses common problems that arise when developing recommendation systems.
Content-Based Recommendation Systems
This module demonstrates how to build a recommendation system using characteristics of the users and items and how to use Qwiklabs to complete each of your labs using Google Cloud.
Collaborative Filtering Recommendations Systems
This module shows how the data of the interactions between users and items from many different users can be combined to improve the quality of predictions.
Neural Networks for Recommendation Systems
This module shows how various recommendation systems can be combined as part of a hybrid approach.
This module presents the goals of reinforcement learning and shows where reinforcement learning fits in machine learning.
This module reviews the topics explored in this course.
- 5 stars67.24%
- 4 stars20.96%
- 3 stars6.11%
- 2 stars2.83%
- 1 star2.83%
TOP REVIEWS FROM RECOMMENDATION SYSTEMS ON GOOGLE CLOUD
I enjoyed this course too much, usually every company wants a recommended system, but the courses or examples available on the web are few. Very well explained many theoretical aspects.
This course and specialization are a great way to learn how to use the Google Cloud Platform with Tensorflow to build cutting edge systems.
It is a wonderful course, to learn about the practical implementation of recommendation systems on Google Cloud Platform.
Had a great experience and learned a lot except some of the labs in the course are misplaced.
Frequently Asked Questions
Can I preview a course before enrolling?
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
What will I get when I enroll?
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
When will I receive my Course Certificate?
If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.
Why can’t I audit this course?
This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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Last Updated: September 1, 2015
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