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Course
- Cloud
Recommendation Systems with TensorFlow on GCP
In this course, you'll apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine.
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.
Table of contents
- Content-Based Recommendation Systems | 1m 52s
- 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
