We going to build a basic model for predicting customer churn using Telco Customer Churn dataset. We're using some classification algorithm to model customers who have left, using Python tools such as pandas for data manipulation and matplotlib for visualizations.

This project focusing on statistical analysis to understand and prepare data for potential machine learning applications. The dataset house_price.csv includes property prices in Bangalore. The analysis aims to perform exploratory data analysis (EDA), detect and handle outliers, check data distribution and normality, and analyze correlations.

Built to learn how to deploy and how one hot encoding works

Insurance charges calculation

An outlier is a data point that is noticeably different from the rest. They represent errors in measurement, bad data collection, or simply show variables not considered when collecting the data.An outlier is a data point that is noticeably different from the rest. They represent errors in measurement, bad data collection, or simply show variabl…