Recommendation Systems on Google Cloud
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.
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- Devise a content-based recommendation engine.
- Implement a collaborative filtering recommendation engine.
- Build a hybrid recommendation engine with user and content embeddings.
- Use reinforcement learning techniques for contextual bandits in the context of recommendations.
• Prior familiarity with foundational machine learning concepts as covered in Machine Learning on Google Cloud. • Familiarity with cloud concepts and fundamentals, networking, security. • Basic proficiency with a scripting language such as Python as covered in the Google Python Crash course. • Basic proficiency with SQL. • Familiarity with Python and TensorFlow.
Aspiring machine learning data analysts, data scientists, data engineers, and programmers interested in learning how to apply machine learning to recommendation systems in practice.
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