In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.
In this project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.
In this project, we are going to work on Deep Learning using H2O to predict Census income.
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
Data Science Project in R-Predict the sales for each department using historical markdown data from the Walmart dataset containing data of 45 Walmart stores.
In this deep learning project, we will predict customer churn using Artificial Neural Networks and learn how to model an ANN in R with the keras deep learning package.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.