Students_Placement_Analysis
The objective of this project is to use certain characteristics of a student such as grades, degrees, major, courses, etc. to predict whether or not the student will be hired and what the salary might be. Thus different steps were followed to realize this project:
- Exploratory Data Analysis (EDA)
- Regression modeling to predict the salary using different Machine Learning algorithms such as Linear Regression, K Nearest Neighbors regression and Random Forest Regression
- Classification modeling to predict whether a student will be placed or not. Some classification algorithms were used such as Random Forest Classifier, Logistic Regression, K Nearest Neighbors Classifier.
Comparisons were made to identify the best algorithm for each problem based on some metrics.