Customer segmentation by Clustering techniques and Predicting the Insurance claim status by using Classification ML models

This project involves the implementation of RFM (Recency, Frequency, Monetary) analysis, a powerful technique in customer segmentation and targeting

Solving the problems by using SMDM

Analyzing e-Commerce company customer churn and providing business recommendations

Hypothesis testing by ANOVA techniques and Dimensionality reduction by Principal Component Analysis

Building various predictive models such as Predicting the price of the product (Linear Regression), Predicting whether employee will opt for holiday package or not (Logistic Regression, Linear Discriminant Analysis))

Election Survey Analysis by Machine Learning

Analyzing and Forecasting of two different Wines' Sales by using Time Series Forecasting modelling

This project involves the implementation of Market Basket Analysis, a powerful technique in retail analytics.