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Building Recommender Systems with Machine Learning and AI

How to create machine learning recommendation systems with deep learning, collaborative filtering, and Python.
4.6 ★★★★★49,337 studentsCreated by Frank Kane, Sundog Education by Frank Kane, Sundog Education TeamLast updated Nov 13, 2025🌐 English

What you'll learn

✓Understand and apply user-based and item-based collaborative filtering to recommend items to users
✓Create recommendations using deep learning at massive scale
✓Build recommendation engines with neural networks and Restricted Boltzmann Machines (RBM's)
✓Make session-based recommendations with recurrent neural networks and Gated Recurrent Units (GRU)
✓Build a framework for testing and evaluating recommendation algorithms with Python
✓Apply the right measurements of a recommender system's success
✓Build recommender systems with matrix factorization methods such as SVD and SVD++
✓Apply real-world learnings from Netflix and YouTube to your own recommendation projects
✓Combine many recommendation algorithms together in hybrid and ensemble approaches
✓Use Apache Spark to compute recommendations at large scale on a cluster
✓Use K-Nearest-Neighbors to recommend items to users
✓Solve the "cold start" problem with content-based recommendations
✓Understand solutions to common issues with large-scale recommender systems

Requirements

•A Windows, Mac, or Linux PC with at least 3GB of free disk space.
•Some experience with a programming or scripting language (preferably Python)
•Some computer science background, and an ability to understand new algorithms.

Description

Frequently Asked Questions

Student Feedback

4.6
★★★★★
Course Rating
75%
15%
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S
Sarah J.
★★★★★2 weeks ago

This course was absolutely amazing! The instructor explained everything clearly and the projects were very helpful.

M
Michael T.
★★★★1 month ago

Great content, highly recommended for beginners. Just wish there were more practice exercises.

D
David K.
★★★★★2 months ago

Best course on this topic I've taken so far. Worth every penny (even better since I got it for free!).

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