此课程适用人群: This course is appropriate for learners who have a basic understanding of statistics. It can be useful both for those exploring applied machine learning and data mining, and for those focused on technology-supported marketing and commerce.


制作方:   明尼苏达大学

  • Joseph A Konstan

    教学方:    Joseph A Konstan, Distinguished McKnight Professor and Distinguished University Teaching Professor

    Computer Science and Engineering

  • Michael D. Ekstrand

    教学方:    Michael D. Ekstrand, Assistant Professor

    Dept. of Computer Science, Boise State University
Basic Info
Course 1 of 5 in the Recommender Systems Specialization.
LevelIntermediate
Commitment4 weeks; an average of 3-7 hours per week, plus 2-5 hours per week for honors track.
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.5 stars
Average User Rating 4.5See what learners said
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Enroll and get full access to every course in the Specialization for 7 days. Cancel any time.
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制作方
明尼苏达大学
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评分和审阅
已评分 4.5,总共 5 个 94 评分

Excelente curso, presenta una vista amplia de técnicas para la implementación de sistemas de recomendación, lo recomiendo totalmente.

Un profesor excelente y un temario muy bueno. También me han gustado mucho las entrevistas y los recorridos por las páginas web que tienen recomendadores.

Exceptional quality.The course content is comprehensive and practical enough applied at workplaces.

Guest lectures are super helpful and assignments are very practical yet make you think.

Thank you Coursera and Minnesota professors for this amazing course and wonderful opportunity for people like me with no background in recommendation systems learn the best research methods and practices in this field.

As a software engineer with computer science background I found that course enhancing my knowledge. I'm going to continue the specialization.