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.
提供方


課程信息
您將學到的內容有
Cluster analysis and segmentation
Collaborative filtering and market basket analysis
Applications of classification- and regression-type prediction models
提供方

加州大学尔湾分校
Since 1965, the University of California, Irvine has combined the strengths of a major research university with the bounty of an incomparable Southern California location. UCI’s unyielding commitment to rigorous academics, cutting-edge research, and leadership and character development makes the campus a driving force for innovation and discovery that serves our local, national and global communities in many ways.
授課大綱 - 您將從這門課程中學到什麼
Cluster Analysis and Segmentation
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.
Collaborative Filtering, Association Rules Mining (Market Basked Analysis)
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.
Classification-Type Prediction Models
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.
Regression-Type Prediction Models
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.
關於 Data Science Fundamentals 專項課程
This specialization demystifies data science and familiarizes learners with key data science skills, techniques, and concepts. The course begins with foundational concepts such as analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, and then moves on to compare data science with classical statistical techniques. The course also provides an overview of the most common techniques used in data science, including data analysis, statistical modeling, data engineering, manipulation of data at scale (big data), algorithms for data mining, data quality, remediation and consistency operations.

常見問題
我什么时候能够访问课程视频和作业?
我订阅此专项课程后会得到什么?
有助学金吗?
還有其他問題嗎?請訪問 學生幫助中心。