University Admission Prediction Using Multiple Linear Regression

In this hands-on guided project, we will train regression models to find the probability of a student getting accepted into a particular university based on their profile. This project could be practically used to get the university acceptance rate for individual students using web application. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

• University Admission Prediction Using Multiple Linear Regression
• In this hands-on project, we will train regression models to find the probability of a student getting accepted into a particular university based on their profile. This project could be practically used to get the university acceptance rate for individual students using web application. In this hands-on project we will go through the following tasks: (1) Understand the Problem Statement, (2) Import libraries and datasets, (3) Perform Exploratory Data Analysis, (4) Perform Data Visualization, (5) Create Training and Testing Datasets, (6) Train and Evaluate a Linear Regression Model, (7) Train and Evaluate an Artificial Neural Network Model, (8) Train and Evaluate a Random Forest Regressor and Decision Tree Model, (9) Understand the various regression KPIs, (10) Calculate and Print Regression model KPIs.