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This is one of the best of investments you can make with regards to career progression and growth in technological knowledge. I was pointed in this direction by a mentor in the IT world who I highly... Read More
Recently I became interested in Hadoop as I think its a great platform for storing and analyzing large structured and unstructured data sets. The experts did a great job not only explaining the... Read More
Customer churn refers to the situation when a customer ends their relationship with a company, and its a costly problem. Customers are the fuel that powers a business.
Loss of customers impacts sales. Further, it’s much more difficult and costly to gain new customers than it is to retain existing customers. As a result, organizations need to focus on reducing customer churn.The good news is that machine learning can help. For many businesses that offer subscription-based services, its critical to both predict customer churn and explain what features relate to customer churn.
Older techniques such as logistic regression can be less accurate than newer techniques such as deep learning, which is why we are going to show you how to model an ANN in R with the keras package.
Learn to classify the sentiment of sentences from the Rotten Tomatoes dataset. You will be asked to label phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive.
In this project, we are going to predict item-level sales data using different forecasting techniques.
Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.