R package for Customer Behavior Analysis
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Updated
Apr 8, 2024 - R
R package for Customer Behavior Analysis
A Data science and Analytics project with the main aim of doing some Descriptive and Exploratory Data Analysis and then applying predictive modelling for predicting why and which are the best and most experienced employees leaving prematurely?
A set of projects I worked on as part of my PG Diploma in Data Science Program
Machine Learning Key Projects
R wrapper for MLJAR API
A Minimalistic Framework for Creating, Managing and Training Multiple Caret Models
Data Mining and Predictive Analytics : Daniel T Larose & Chantal D Larose Wiley
Codes written in the course of a data science workshop at KIT in cooperation with FZI
Analyzing transactions of a retailer to predict promotional items.
Extensive Analysis and Prediction on the Bank Marketing Dataset.
A predictive model that leverages classification models such as Random Forest and Naive Bayes to predict customer churn
Stock Portfolio Performance by Weighted Stock Selection - The project quantitatively predicts the factors that must be given the most and least weights to obtain obtain the highest returns, risk and win-rates while developing a S&P500 portfolio
Survival modelling using Cox proportional hazard regression model
Analytical tool to help the company decide whether the employee will stay or not
Predictive Analytics using R programming
The feature of interest is whether or not a customer buys a caravan insurance, based on socio-demographic factors and ownership of other insurance policies; and to build profile of a typical customer.
This is a machine learning case study used to predict the potential earnings of people in R for a given dataset.
A shiny web application template for advanced interactive and predictive data analytics for time series.
Predicting Hospital Readmission of Diabetics | Medical Insurance Cost with EDA + OLS Regression | Predicting Customer Risk by Home Equity Loan | CLICK TO SEE MORE
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