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
Dieser Kurs ist Teil von Spezialisierung Advanced Machine Learning on Google Cloud
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Was Sie lernen werden
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.
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In diesem Kurs gibt es 7 Module
This module previews the topics covered in the course.
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1 Video1 Lektüre
This module defines what recommendation systems are, reviews the different types of recommendation systems, and discusses common problems that arise when developing recommendation systems.
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5 Videos1 Lektüre
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.
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10 Videos1 Lektüre
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.
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13 Videos1 Lektüre
This module shows how various recommendation systems can be combined as part of a hybrid approach.
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13 Videos1 Lektüre
This module presents the goals of reinforcement learning and shows where reinforcement learning fits in machine learning.
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10 Videos1 Lektüre
This module reviews the topics explored in this course.
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2 Videos1 Lektüre
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Last Updated: September 1, 2015