Recommender Systems Specialization

开始时间: 04/23/2018 持续时间: Unknown

所在平台: Coursera专项课程

课程类别: 计算机科学

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/specializations/recommender-systems

Explore 1600+ online courses from top universities. Join Coursera today to learn data science, programming, business strategy, and more.

课程评论:没有评论

第一个写评论        关注课程

课程详情

This Specialization covers all the fundamental techniques in recommender systems, from non-personalized and project-association recommenders through content-based and collaborative techniques. Designed to serve both the data mining expert and the data literate marketing professional, the courses offer interactive, spreadsheet-based exercises to master different algorithms along with an honors track where learners can go into greater depth using the LensKit open source toolkit. A Capstone Project brings together the course material with a realistic recommender design and analysis project.

课程大纲

5 courses

Introduction to Recommender Systems: Non-Personalized and Content-Based
Upcoming session: Apr 23
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

Nearest Neighbor Collaborative Filtering
Upcoming session: Apr 16
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 simila

Recommender Systems: Evaluation and Metrics
Upcoming session: Apr 23
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,

Matrix Factorization and Advanced Techniques
Upcoming session: Apr 16
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 rec

Recommender Systems Capstone
Upcoming session: Apr 16
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 ca

课程评论(0条)

Deep Learning Specialization on Coursera

课程简介

明尼苏达大学的推荐系统专项课程系列(Recommender Systems Specialization),这个系列由4门子课程和1门毕业项目课程组成,包括推荐系统导论,最近邻协同过滤,推荐系统评价,矩阵分解和高级技术等,感兴趣的同学可以关注:Master Recommender Systems-Learn to design, build, and evaluate recommender systems for commerce and content.

课程标签

推荐系统 推荐系统课程 推荐系统导论 最近邻协同过滤 推荐系统评价 矩阵分解 协同过滤

20人关注该课程

主题相关的课程