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.
In this project, we are going to work on Deep Learning using H2O to predict Census income.
Data science project in R to develop automated methods for predicting the cost and severity of insurance claims.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
Deep Learning Project- Learn about implementation of a machine learning algorithm using autoencoders for anomaly detection.
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 data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.
Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual 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.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.