This repo contains code and resources for random analysis projects done in R, using multiple packages such as tidyverse, tidymodels and more. Note that project files are added on an ongoing basis. Additionally, data folders and artifacts (like model objects) are not committed to this repo to avoid push conflicts due to large files.
This project focuses on analyzing Starbucks ingredients and utilizing machine learning techniques to predict the calorie content of a drink based on its ingredients.
The project explores customer segmentation in the banking industry using the k-means algorithm. It aims to identify distinct customer segments based on shared characteristics and provides insights into effective customer targeting in the banking sector. See detailed analysis write up here.
A detailed analysis of CRM data from a company selling computer hardware. The primary focus was on establishing performance benchmarks, understanding sales trends, and segmenting customers to enhance sales and marketing strategies. Read the analysis write up on Medium.