Files in this item

FilesDescriptionFormat

application/vnd.openxmlformats-officedocument.presentationml.presentation

application/vnd.openxmlformats-officedocument.presentationml.presentationTED Talks – A P ... sification Algorithms.pptx (1MB)
(no description provided)Microsoft PowerPoint 2007

Description

Title:TED Talks – A Predictive Analysis Using Classification Algorithms
Author(s):Paulami Ray; Kumkum Yadav; Garima Garg
Subject(s):Classification algorithms
Machine learning
Data Mining
Logistic Regression
Support Vector Machine
KNN
Naive Bayes
Abstract:TED talks are a great source of knowledge and ideas which are available online for free. TED talk encompasses a plethora of topics like Technology, Entertainment, Design, Cultural, Academic Research etc. which are presented by different speakers. The purpose of this study is to develop a model to predict two things – firstly, to predict the number of views for the talks and secondly, to predict the overall reaction of the talks from the description of the comments given by the users. We have used several machine learning classification algorithms like SVM, Logistic Regression, Random Forest, Decision tree and KNN. The dataset for this project includes details of 2550 TED Talks from 2006 to 2017. We have also done some visualizations on the data set to get more understanding of the topic and analyze it further.
Issue Date:2018-04-24
Publisher:University of Illinois at Urbana-Champaign School of Information Sciences
Citation Info:P. Ray, K. Yadav, G. Garg.TED Talks – A Predictive Analysis Using Classification Algorithms. University of Illinois at Urbana-Champaign School of Information Sciences, April 24, 2018.
Genre:oral history
Conference Poster
Type:Other
Language:English
URI:http://hdl.handle.net/2142/99922
Sponsor:University of Illinois at Urbana-Champaign School of Information Sciences
Date Available in IDEALS:2018-05-11


This item appears in the following Collection(s)

Item Statistics