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Recommendation Systems with TensorFlow on GCP

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Free Online Course: Recommendation Systems with TensorFlow on GCP provided by Coursera is a comprehensive online course, which lasts for 2 weeks long, 15 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from Coursera. Recommendation Systems with TensorFlow on GCP is taught by Google Cloud Training.

Google Cloud via Coursera
2 weeks long, 15 hours worth of material
Upcoming
Overview

  • 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.

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