Welcome to Cluster Analysis, Association Mining, and Model Evaluation. In this course we will begin with an exploration of cluster analysis and segmentation, and discuss how techniques such as collaborative filtering and association rules mining can be applied. We will also explain how a model can be evaluated for performance, and review the differences in analysis types and when to apply them.
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Cluster Analysis, Association Mining, and Model Evaluation
This course is part of Data Science Fundamentals Specialization
Taught in English
Some content may not be translated
![Julie Pai](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://coursera-instructor-photos.s3.amazonaws.com/14/6d0f0a822f48539c3219bc76c28416/_JP-Headshot.jpg?auto=format%2Ccompress&dpr=1&w=75&h=75&fit=crop)
Instructor: Julie Pai
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(34 reviews)
What you'll learn
Cluster analysis and segmentation
Collaborative filtering and market basket analysis
Applications of classification- and regression-type prediction models
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There are 4 modules in this course
Welcome to Module 1, Cluster Analysis and Segmentation. In this module we will explore cluster analysis, a popular unsupervised learning algorithm. We will also review the two major styles of cluster analysis, and discuss potential applications to different industries.
What's included
2 readings1 discussion prompt
Welcome to Module 2, Collaborative Filtering, Association Rules Mining, & Market Basket Analysis. In this module we will begin with an explanation of collaborative filtering and association rules mining, and how these techniques are used to make automatic predictions. We will also take a closer look at the various common applications of market basket analysis.
What's included
1 video1 reading1 quiz
Welcome to Module 3, Classification-Type Prediction Models. In this module we will begin with an explanation of how classification-type prediction models are evaluated for performance, and how a confusion matrix can help visualize that performance. We will also discuss the applicability of cluster analysis, and how it can be used to detect rare events such as fraudulent transactions.
What's included
1 video2 readings1 discussion prompt
Welcome to Module 4, Regression-Type Prediction Models. In this module we will review how regression analytics are used for both hypothesis testing and prediction, and how a scatter plot can be leveraged to better understand the relationship between two variables. We will also discuss the differences between correlation analysis and a regression analysis, and a look at simple vs multiple regression.
What's included
1 reading1 quiz1 discussion prompt
Instructor
![Julie Pai](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://coursera-instructor-photos.s3.amazonaws.com/14/6d0f0a822f48539c3219bc76c28416/_JP-Headshot.jpg?auto=format%2Ccompress&dpr=1&w=75&h=75&fit=crop)
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University of California, Irvine
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