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Each project comes with 2-5 hours of micro-videos explaining the solution.
Get access to 50+ solved projects with iPython notebooks and datasets.
Add project experience to your Linkedin/Github profiles.
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.
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.
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset​ using Keras in Python.
In this deep learning project, we are going to predict which team will win the NCAA basketball tournament of coming 2017 based on past historical data.