International Journal of Emerging Trends & Technology in Computer Science
A Motivation for Recent Innovation & Research
ISSN 2278-6856
www.ijettcs.org

Call for Paper, Published Articles, Indexing Infromation Exploratory Data Analysis and Visualisation of YouTube Trending Videos using Machine Learning Techniques, Authors : Saba Arfiya , Dr. Mallamma V Reddy , Naveen Kumar T.R, International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), www.ijettcs.org
Volume & Issue no: Volume 11, Issue 4, July - August 2022

Title:
Exploratory Data Analysis and Visualisation of YouTube Trending Videos using Machine Learning Techniques
Author Name:
Saba Arfiya , Dr. Mallamma V Reddy , Naveen Kumar T.R
Abstract:
Abstract The online video streaming capacities are very trending and profoundly in recent generations demand over multimedia communications. A video to attain to maximum human beings, YouTube gives a trending net page on internet website that shows movies which might be trending at that precise time. The tending portion of videos depends on various factors like high subscriber’s likes, views and shares and videos should get the popularity as viral. The objective of the project mainly deals with the Exploratory Data Analysis (EDA) and visualization of YouTube Statistics on Trending videos globally. The exploration is prepared by customer satisfactory topographies such as video Views, Comments, Report, Likes and Dislikes. The graphical analysis can be achieved by means of EDA, Data Visualisation and plotting. We have used Machine Learning algorithms mainly Linear Regression, Random Forest Regressor and Gradient Boosting Regressor and making the predictions on Views and Likes on YouTube Indian recent trending Dataset. Accuracy of the models for Linear Regression, Random Forest Regressor and Gradient Boosting Regressor are 71%, 54% and 73% respectively.
Cite this article:
Saba Arfiya , Dr. Mallamma V Reddy , Naveen Kumar T.R , " Exploratory Data Analysis and Visualisation of YouTube Trending Videos using Machine Learning Techniques " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 11, Issue 4, July - August 2022 , pp. 103-107 , ISSN 2278-6856.
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