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Wine tasting is a unique profession, it is usually difficult to predict what the customer would like, based on the past preferences, hence in this machine learning project before recommending any particular variety of wine to the customer if we can identify their preferences using data mining processing from the physiochemical properties of the wines, it would be easier for the restaurant to recommend wines. This machine learning project example can be taken to other similar products that can help in target marketing by modeling consumer tastes from niche markets.
Wine dataset is considered for this R machine learning project, with white and red vinho verde samples (from Portugal)
In this data science project, you will learn to predict churn on a built-in dataset using Ensemble Methods in R.
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.
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.