In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
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.
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 machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
In this machine learning and IoT project, we are going to test out the experimental data using various predictive models and train the models and break the energy usage.
In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.
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 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.
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.