Recommendation Systems on Google Cloud

In this course, you 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.

• 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.
• Reinforcement Learning
• This module presents the goals of reinforcement learning and shows where reinforcement learning fits in machine learning.
• Summary
• This module reviews the topics explored in this course.