In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.
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.
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.
Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
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 machine learning churn project, we implement a churn prediction model in python using ensemble techniques.