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数据可视化, 伊利诺伊大学香槟分校

4.5
748 个评分
173 个审阅

课程信息

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based classification and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns....

热门审阅

创建者 MK

Apr 06, 2018

Good course, very well structured and with interesting assignments. Some (especially first) lessons are more of a general culture but most are very helpful and allow to learn a lot of things.

创建者 JM

Jun 04, 2016

I found the class to be very informative. The assignments on creating charts and graphs for large data sets were practical and helped me understand the concepts taught in the course.

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168 个审阅

创建者 Павлов Юрий Андреевич

Apr 17, 2019

COoOooOOoL

创建者 Hamreet singh

Mar 29, 2019

nice

创建者 Shuo Jiang

Mar 23, 2019

some assignments are boring. but in general, its good

创建者 Yogesh Bharadwaj CHICKMAGALUR ANANTHA SWAMY

Mar 07, 2019

Very good knowledge on visualization. Never though these many indepth concepts are involved in visualizations.

创建者 Brandi Rose

Feb 25, 2019

Interesting course for getting started with complex graphing principles. The instructor was easy to follo

创建者 Morla Mohan Sai

Feb 25, 2019

Good course

创建者 Юхновский Илья Александрович

Feb 17, 2019

I like it! Very useful!

创建者 liz arnold

Feb 11, 2019

it is good.,

创建者 Marco Bonvini

Feb 06, 2019

Very useful course for beginners.

Pdf of the slides not available

Low interaction with other students, mentor answering the forum a bit bizarre

创建者 Chen Qiu

Feb 04, 2019

The fundamental concept part and assignments are good.

But I think since it is related to visualization, the course can spend more time on how to make a visual.