In this machine learning churn project, we implement a churn prediction model in python using ensemble 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.
In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.
In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
In this R data science project, we will explore wine dataset to assess red wine quality. The objective of this data science project is to explore which chemical properties will influence the quality of red wines.
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 project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
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 data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.