In this hands-on project, we will train Logistic regression and XG-Boost models to predict whether a particular person earns less than 50,000 US Dollars or more than 50,000 US Dollars annually. This data was obtained from U.S. Census database and consists of features like occupation, age, native country, capital gain, education, and work class.

The hands-on project on Logistic Regression101: US Income Classification is divided into the following tasks:
Understand the problem statement and business case Import libraries/datasets
Perform Exploratory Data Analysis Perform Data Visualization
Prepare the data before model training
Understand the intuition behind Logistic Regression
Train and Evaluate a Logistic regression model
Train and Evaluate a XG-Boost model