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Course
- Cloud
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
- Content-based Recommendation Systems | 10s
- Content-Based Recommendation Systems | 1m 40s
- Similarity Measures | 3m 16s
- Building a User Vector | 3m 42s
- Making Recommendations Using a User Vector | 1m 44s
- Making Recommendations for Many Users | 6m 50s
- Lab intro:Create a Content-Based Recommendation System | 20s
- Lab: Content-Based Filtering by Hand | 10s
- Lab Solution:Create a Content-Based Recommendation System | 13m 57s
- Using Neural Networks for Content-Based Recommendation Systems | 4m 7s
- Lab Intro:Create a Content-Based Recommendation System Using a Neural Network | 35s
- Lab: Content-Based Filtering using Neural Networks | 10s
- Lab Solution:Create a Content-Based Recommendation System Using a Neural Network | 36m 36s
