Search result for Courses taught by Michael D. Ekstrand
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Recommender Systems: Evaluation and Metrics
by Michael D. Ekstrand , Joseph A Konstan- 4.4
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Approx. 7 hours to complete
In this course you will learn how to evaluate recommender systems. You will gain familiarity with several families of metrics, including ones to measure prediction accuracy, rank accuracy, decision-support, and other factors such as diversity, product coverage, and serendipity. You will learn how different metrics relate to different user goals and business goals....
Recommender Systems Capstone
by Michael D. Ekstrand , Joseph A Konstan- 0.0
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Approx. 3 hours to complete
This capstone project course for the Recommender Systems Specialization brings together everything you've learned about recommender systems algorithms and evaluation into a comprehensive recommender analysis and design project. You will be given a case study to complete where you have to select and justify the design of a recommender system through analysis of recommender goals and algorithm performance....
Introduction to Recommender Systems: Non-Personalized and Content-Based
by Joseph A Konstan , Michael D. Ekstrand- 4.5
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Approx. 23 hours to complete
This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations. Preface Intro to Recommender Systems...
Nearest Neighbor Collaborative Filtering
by Joseph A Konstan , Michael D. Ekstrand- 4.3
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Approx. 15 hours to complete
In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. Preface Course Introduction Course Structure Outline...
Matrix Factorization and Advanced Techniques
by Michael D. Ekstrand , Joseph A Konstan- 4.3
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Approx. 16 hours to complete
In this course you will learn a variety of matrix factorization and hybrid machine learning techniques for recommender systems. Starting with basic matrix factorization, you will understand both the intuition and the practical details of building recommender systems based on reducing the dimensionality of the user-product preference space. Preface Matrix Factorization and Advanced Techniques...
Top Online Courses and Specializations | Coursera
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Find Courses and Specializations from top universities like Yale, Michigan, Stanford, and leading companies like Google and IBM. Join Coursera for free and transform your career with degrees, certificates, Specializations, & MOOCs in data science, computer science, business, and dozens of other topics....
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Learn online and earn valuable credentials from top universities like Yale, Michigan, Stanford, and leading companies like Google and IBM. Join Coursera for free and transform your career with degrees, certificates, Specializations, & MOOCs in data science, computer science, business, and dozens of other topics....
Course Definition & Meaning - Merriam-Webster
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course: [noun] the act or action of moving in a path from point to point....
Free Online Courses | Stanford Online
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Free Online Courses. Our free online courses provide you with an affordable and flexible way to learn new skills and study new and emerging topics. Learn from Stanford instructors and industry experts at no cost to you....
Online Courses - Learn Anything, On Your Schedule | Udemy
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Udemy is an online learning and teaching marketplace with over 185,000 courses and 49 million students. Learn programming, marketing, data science and more....
Courses » Academics | Boston University
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Courses. The listing of a course description here does not guarantee a course’s being offered in a particular semester. Please refer to the published schedule of classes on the Student Link for confirmation a class is actually being taught and for specific course meeting dates and times....
