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Building Recommender Systems with Machine Learning and AI

You're reading from Building Recommender Systems with Machine Learning and AI Get started with building intelligent recommender systems

Product type Video

Published in Sep 2018

Last Updated in Oct 2022

Publisher Packt

ISBN-13 9781789803273

Length 11hrs 24mins

Edition 1st Edition

Languages

Python

Tools

Anaconda

Concepts

Machine Learning

Author (1):

Frank Kane

View More author details

Table of Contents (14) Chapters

1. Getting Started

2. Introduction to Python FREE CHAPTER

3. Evaluating a Recommender System

4. A Recommender Engine Framework

5. Content-Based Filtering

6. Neighborhood-Based Collaborative Filtering

7. Matrix Factorization Methods

8. Introduction to Deep Learning (Optional)

9. Deep Learning for Recommender Systems

10. Scaling It Up

11. Real-World Challenges of Recommender Systems

12. Case Studies

13. Hybrid Approaches

14. Wrapping Up

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Authors (1)

Frank Kane

Frank Kane

Frank Kane has spent nine years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers all the time. He holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology and teaches others about big data analysis.

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