Understanding Algorithms for Recommendation Systems

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Cost $29/mo
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Understanding Algorithms for Recommendation Systems

Course Details

Cost

$29/mo

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Upcoming Schedule

  • On demand

Course Provider

Pluralsight online courses
Pluralsight's mission is to publish high quality online training courses for professional developers, IT admins and creative artists. Over 750,000 Learners have already made use of the 3,500+ Courses available in this extensive library. Pluralsight delivers world-class training that¹s easy to comprehend and quick to learn. That¹s the beauty of being taught by experts. Course authors are an elite group of tech and creative professionals, innovators and leaders. As a subscriber, you are ...
Pluralsight's mission is to publish high quality online training courses for professional developers, IT admins and creative artists. Over 750,000 Learners have already made use of the 3,500+ Courses available in this extensive library. Pluralsight delivers world-class training that¹s easy to comprehend and quick to learn. That¹s the beauty of being taught by experts. Course authors are an elite group of tech and creative professionals, innovators and leaders. As a subscriber, you are connected with authors through discussion boards for ongoing, real-time learning. Courses give you the experience and skills you need to succeed on the job and grow your career. With downloadable exercise files, you can follow along with the video to practice applying your new skills. Pre- and post-course assessments track your progress. When you successfully complete a course, we you receive a certificate and an official transcript to validate and build your online resume.

Provider Subject Specialization
Sciences & Technology
Business & Management
5 reviews

Course Description

In addition to monetizing user behavior data, recommendation algorithms also help extract actionable recommendations from raw user ratings/purchases data. This course, Understanding Algorithms for Recommendation Systems, will cover the different types of Recommendation algorithms - Content-Based Filtering, Collaborative Filtering, and Association Rules Learning and when to use each of these types. You'll also learn about the specific algorithms such as the Nearest Neighbors model, Latent Factor Analysis and the Apriori Algorithm and implement them on real data sets. Finally, you'll learn about mining for rules that relate different products. By the end of this course, you'll be able to choose the recommendation algorithm that fits your problem and dataset, and apply it to find relevant recommendations.
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