Analyzing on Time Frame Data : Youtube Trending Video Dataset Analysis | Python | Data Analyst
YouTube generates an immense amount of data every second, encompassing videos, comments, likes, and much more. In this video, our focus is on analyzing trending video data. By leveraging this data, In this video we aim to perform a comprehensive analysis with several key objectives:
1. Trend Analysis: We will examine which videos are trending and identify any common characteristics among them, such as their category, the channels they come from, or the tags associated with them.
2. Publish Time Analysis: We will explore whether the timing of a video's publication—including the day of the week and time of day—has any impact on its popularity or the likelihood of it becoming a trending video.
3. Text Analysis of Video Titles and Descriptions: We will conduct text analysis on the titles and descriptions of trending videos to uncover prevalent keywords or themes.
Throughout this hands-on experience, we'll learn powerful machine
learning algorithms, including linear regression, KNN, MultinomialNB,
and logistic regression. Additionally, we'll explore the art of data
visualization using tools like Pyplot and Seaborn. So sit back, relax,
and enhance your Machine Learning skills with us!
Materials / References:
Github Codes and Datasets (give it a star ⭐):
Youtube analysis - https://github.com/mendsalbert/Youtub...
Visual Studio website - https://code.visualstudio.com/
Python official website - https://www.python.org/
In this single video, you'll Learn how to analyse :
1. Trend Analysis: We will examine which videos are trending and identify any common characteristics among them, such as their category, the channels they come from, or the tags associated with them.
2. Publish Time Analysis: We will explore whether the timing of a video's publication—including the day of the week and time of day—has any impact on its popularity or the likelihood of it becoming a trending video.
3. Text Analysis of Video Titles and Descriptions: We will conduct text analysis on the titles and descriptions of trending videos to uncover prevalent keywords or themes.
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