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 in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.
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.
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.
Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.
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.
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.
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.
Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.