Prediction the Electronic Gadget Addiction of Students using Machine Learning | AI Project

Prediction the Electronic Gadget Addiction of Students using Machine Learning | AI Project
To get This Project 👉- https://www.ieeexpert.com/?p=2661

🔥 Our Proposed Project Title: Prediction the Electronic Gadget Addiction of Students using Machine Learning
🔍Implementation: Python.
🧠Algorithm / Model Used: Random Forest
🎯Web Framework: Flask.
💻Frontend: HTML, CSS, JavaScript.

ABSTRACT
The widespread use of electronic gadgets among students has raised concerns about the potential negative impacts on their academic performance, mental health, and overall well-being.
This project aims to develop a predictive model using machine learning to analyze and forecast the effects of gadget addiction on students' lives.
By leveraging data such as screen time, academic records, sleep patterns, and social interactions, we explore the correlations and patterns that link excessive gadget use to adverse outcomes.
The project employs machine learning techniques, including random Forest, to build models capable of predicting the likelihood and severity of addiction-related consequences.
Our findings indicate that certain behavioral and academic indicators can reliably predict the impact of gadget addiction, offering an accuracy rate of over 97% with the most sophisticated models.


More Projects - https://bit.ly/495LVbb
Contact us on - +91 9363932473

Ieee Xpert, India. The Best Bulk Service Provider for IEEE Solutions
Including Packages
=======================
* Base Paper
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Readme File


* Addons
* Video Tutorials
* Supporting Softwares

Specialization
=======================
* 24/7 Support


In this intriguing video, we explore the fascinating intersection of technology and education by predicting student gadget addiction using machine learning techniques. As students increasingly rely on gadgets for learning and leisure, understanding their usage patterns becomes crucial. Join us as we delve into the methodologies used to analyze data, identify addiction trends, and predict future behaviors among students. We'll cover the types of data collected, the machine learning algorithms implemented, and the insights gained from our analysis. Whether you're an educator, a parent, or a tech enthusiast, this video will provide valuable insights into the impact of gadget usage on student life. Don’t forget to like, comment, and subscribe for more content on technology and education! #MachineLearning #GadgetAddiction #StudentLife #DataAnalysis #EducationTech #PredictiveAnalytics #techineducation
Gadget Addiction Prediction, Student Gadget Usage, Machine Learning Addiction Prediction, Predicting Student Behavior, ML Student Addiction Model, Machine Learning Student Health, AI in Education, machine learning projects,machine learning projects in python, machine learning projects for beginners,machine learning projects with code,machine learning projects for final year,machine learning projects 2024,ieee expert

00:00 Introduction
03:09 Reference paper
04:29 PPT Explanation
06:41 Proposed Solution
07:18 Overall Architecture
11:03 Dataset Collection
11:40 Project Demo
17:43 Conclusion