(ML)

📖 Presentation Material

⭐️ 프로젝트 개요

This project aims to combine various ML techniques (data preprocessing, algorithms, evaluation) to visualize and confirm study results when students study through a remote learning system.

The goal is to discover the optimal combination of ML techniques.

By inputting a student's study environment, it is possible to check the student's expected academic achievement.

1) Source and explanation on the dataset

Dataset name : Students Adaptability Level in Online Education

https://www.kaggle.com/datasets?search=students&sort=votes

Original Research Paper : Students' Adaptability Level Prediction in Online Education using Machine Learning Approaches

https://www.researchgate.net/publication/355891881_Students'_Adaptability_Level_Prediction_in_Online_Education_using_Machine_Learning_Approaches

Predict The Adaptivity Level of Students by various Features

• The feature sets :

Gender Age Education Level Institution Type IT Student Location in Town Load-shedding Financial Condition Internet Type Network Type Class Duration Self LMS Device

• The target feature

Adaptivity level

2) Objective of your analysis

1. Because of COVID situation, classes are being held non-face-to-face
2. We would like to use this dataset to see how students are taking classes in non-face-to-face situations.
3. Also, we would like to predict how students' non-face-to-face class environment and grades are related.

3. Finally, we would like to find top five and best combination to predict the datas

👬 Team Composition

ML(2), PPT(1), 발표(1)

🔨 Role and Function

I was solely responsible for the overall functionality development.

⚒️ Used Technologies and Libraries

Linear Regression

Logistic Regression

Decision Tree

KNN Classifier

Random Forest