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Recommendation Systems on Google Cloud
  • Level Expert
  • Duration 15 hours
  • Course by Google Cloud
  • Offered by

About

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.

Modules

Welcome to Recommendation Systems on Google Cloud

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Welcome to Recommendation Systems on Google Cloud

1 Readings

  • How to Send Feedback

Recommendation Systems Overview

    • 5 Videos
    • 1 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Recommendation Systems Overview

1 Discussions

  • Designing a Recommendation System

5 Videos

  • Introduction
  • Types of Recommendation Systems
  • Content-Based or Collaborative
  • Recommendation System Pitfalls
  • Discussion

1 Readings

  • Recommendation Systems Overview

Introduction

    • 7 Videos
    • 1 ExternalTool
Show info about module content

1 External Tool

  • Lab: Content-Based Filtering by Hand

7 Videos

  • Content-Based Recommendation Systems
  • Similarity Measures
  • Building a User Vector
  • Making Recommendations Using a User Vector
  • Making Recommendations for Many Users
  • Lab intro: Create a Content-Based Recommendation System
  • Getting Started with Google Cloud and Qwiklabs

Building a Content-Based Recommendation System with a Neural Network

    • 2 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Content-Based Recommendation Systems

2 Videos

  • Using Neural Networks for Content-Based Recommendation Systems
  • Summary

1 Readings

  • Content-Based Recommendation Systems

ALS, a Matrix Factorization Algorithm For Collaborative Filtering

    • 5 Videos
Show info about module content

5 Videos

  • Types of User Feedback Data
  • Embedding Users and Items
  • Factorization Approaches
  • The ALS Algorithm
  • Preparing Input Data for ALS

Implementing ALS in TensorFlow

    • 8 Videos
    • 1 Readings
    • 1 ExternalTool
    • 1 Assignment
Show info about module content

1 Assignment

  • Collaborative Filtering Recommendations Systems

1 External Tool

  • Lab: Collaborative filtering on Google Analytics Data

8 Videos

  • Creating Sparse Tensors For Efficient WALS Input
  • Instantiating a WALS Estimator: From Input to Estimator
  • Instantiating a WAL Estimator: Decoding TFRecords
  • Instantiating a WALS Estimator: Recovering Keys
  • Instantiating a WALS Estimator: Training and Prediction
  • Lab Intro: Collaborative Filtering with Google Analytics Data
  • Issues with Collaborative Filtering
  • Cold Starts

1 Readings

  • Collaborative Filtering Recommendations Systems

Introduction

    • 5 Videos
    • 1 ExternalTool
Show info about module content

1 External Tool

  • Lab: ML on GCP - Hybrid Recommendations with the MovieLens Dataset

5 Videos

  • Hybrid Recommendation Systems
  • Lab Intro: Designing a Hybrid Recommendation System
  • Lab Intro: Designing a Hybrid Collaborative Filtering Recommendation System
  • Lab Intro: Designing a Hybrid Knowledge-based Recommendation System
  • Lab Intro: Building a Neural Network Hybrid Recommendation System

Incorporating Context

    • 8 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Neural Networks for Recommendations

8 Videos

  • Context-Aware Recommendation Systems
  • Context-Aware Algorithms
  • Contextual Postfiltering
  • Modeling Using Context-Aware Algorithms
  • YouTube Recommendation System Case Study: Overview
  • YouTube Recommendation System Case Study: Candidate Generation
  • YouTube Recommendation System Case Study: Ranking
  • Summary

1 Readings

  • Neural Networks for Recommendation Systems

Introduction

    • 8 Videos
Show info about module content

8 Videos

  • Introduction to module
  • Introduction to Reinforcement Learning
  • The reinforcement learning framework and workflow
  • Model-based and model-free reinforcement learning
  • Value-based reinforcement learning
  • Policy-based reinforcement learning
  • Contextual bandits
  • Applications of reinforcement learning

Quiz: Reinforcement Learning

    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Reinforcement Learning

1 Readings

  • Reinforcement Learning

Lab

    • 2 Videos
    • 1 ExternalTool
Show info about module content

1 External Tool

  • Lab: Applying Reinforcement Learning

2 Videos

  • Lab Intro
  • Lab Review

Summary

    • 2 Videos
    • 1 Readings
Show info about module content

2 Videos

  • Course Summary
  • Specialization Summary

1 Readings

  • All Course Readings

Auto Summary

Unlock the power of recommendation systems with the fifth and final course in the Advanced Machine Learning on Google Cloud series. Designed for experts in Data Science & AI, this Coursera course guides you through building a machine learning pipeline for recommendation engines. Dive deep into classification models and embeddings over a 900-minute duration. Choose from Starter, Professional, or Paid subscription options to elevate your skills in this specialized field. Perfect for advanced learners aiming to master recommendation systems on Google Cloud.

Google Cloud Training
Instructor

Google Cloud Training