Recommendation Systems with TensorFlow on Google Cloud
In this course, you'll 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.
What you'll learn
In this course, you'll 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.
Table of contents
Recommendation Systems Overview
30mins
Content-Based Recommendation Systems
74mins
- Content-based Recommendation Systems 0m
- Content-Based Recommendation Systems 2m
- Similarity Measures 3m
- Building a User Vector 4m
- Making Recommendations Using a User Vector 2m
- Making Recommendations for Many Users 7m
- Lab intro:Create a Content-Based Recommendation System 0m
- Lab: Content-Based Filtering by Hand 0m
- Lab Solution:Create a Content-Based Recommendation System 14m
- Using Neural Networks for Content-Based Recommendation Systems 4m
- Lab Intro:Create a Content-Based Recommendation System Using a Neural Network 1m
- Lab: Content-Based Filtering using Neural Networks 0m
- Lab Solution:Create a Content-Based Recommendation System Using a Neural Network 37m
Collaborative Filtering Recommendation Systems
146mins
- Collaborative Filtering 0m
- Types of User Feedback Data 7m
- Embedding Users and Items 13m
- Factorization Approaches 7m
- The ALS Algorithm 5m
- Preparing Input Data for ALS 6m
- Creating Sparse Tensors For Efficient WALS Input 3m
- Instantiating a WALS Estimator:From Input to Estimator 5m
- Instantiating a WAL Estimator:Decoding TFRecords 4m
- Instantiating a WALS Estimator:Recovering Keys 13m
- Instantiating a WALS Estimator:Training and Prediction 6m
- Lab Intro:Collaborative Filtering with Google Analytics Data 1m
- Lab: Collaborative Filtering on Google Analytics data 0m
- Lab Solution:Collaborative Filtering with Google Analytics Data 44m
- Issues with Collaborative Filtering 4m
- Productionized WALS Demo 22m
- Cold Starts 6m
Neural Networks for Recommendation Systems
97mins
- Neural Networks for Recommendation Systems 0m
- Hybrid Recommendation Systems 15m
- Lab:Designing a Hybrid Recommendation System 6m
- Lab:Designing a Hybrid Collaborative Filtering Recommendation System 4m
- Lab:Designing a Hybrid Knowledge-based Recommendation System 5m
- Lab Intro:Building a Neural Network Hybrid Recommendation System 0m
- Lab: ML on GCP: Hybrid Recommendations with the MovieLens Dataset 0m
- Lab Solution:Building a Neural Network Hybrid Recommendation System 35m
- Context-Aware Recommendation Systems 8m
- Context-Aware Algorithms 5m
- Contextual Postfiltering 3m
- Modeling Using Context-Aware Algorithms 5m
- YouTube Recommendation System Case Study:Overview 3m
- YouTube Recommendation System Case Study:Candidate Generation 3m
- YouTube Recommendation System Case Study:Ranking 3m
- Summary 2m
Building an End-to-End Recommendation System
49mins
- Building an End-to-End Recommendation System 0m
- Introduction 4m
- Architecture Overview 3m
- Cloud Composer Overview 16m
- Cloud Composer:DAGs 5m
- Cloud Composer:Operators for ML 9m
- Cloud Composer:Scheduling 2m
- Cloud Composer:Triggering Workflows with Cloud Functions 4m
- Cloud Composer:Monitoring and Logging 5m
- Lab Intro:End-to-End Recommendation System 1m
- Lab: End to End Recommendation System 0m
Summary
8mins