Overview
Class Central Tips
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.
Syllabus
- 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.
Taught by
Google Cloud Training