- Course
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.
Beginner
- Course
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.
Beginner
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This course is included in the libraries shown below:
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What you'll learn
This course content has now been retired on Pluralsight and will be removed by the end of 2026
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In this course, you'll apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine.
Recommendation Systems with TensorFlow on GCP
Beginner
Table of contents
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Content-Based Recommendation Systems | 1m 52s
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Similarity Measures | 3m 16s
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Building a User Vector | 3m 42s
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Making Recommendations Using a User Vector | 1m 44s
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Making Recommendations for Many Users | 6m 50s
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Lab intro: Create a Content-Based Recommendation System | 20s
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Lab: Content-Based Filtering by Hand | 10s
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Lab Solution:Create a Content-Based Recommendation System | 13m 57s
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Using Neural Networks for Content-Based Recommendation Systems | 4m 7s
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Lab Intro: Create a Content-Based Recommendation System Using a Neural Network | 35s
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Lab: Content-Based Filtering using Neural Networks | 10s
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Lab Solution:Create a Content-Based Recommendation System Using a Neural Network | 36m 36s
