In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
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.
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.
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 machine learning churn project, we implement a churn prediction model in python using ensemble techniques.
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.
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.
There are different time series forecasting methods to forecast stock price, demand etc. In this machine learning project, you will learn to determine which forecasting method to be used when and how to apply with time series forecasting example.
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 machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.