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I have extensive experience in data management and data processing. Over the past few years I saw the data management technology transition into the Big Data ecosystem and I needed to follow suit. I... Read More
My Interaction was very short but left a positive impression. I enrolled and asked for a refund since I could not find the time. What happened next: They initiated Refund immediately. Their... Read More
Customer satisfaction is a key measure of success. Unhappy customers don't stick around. What's more, unhappy customers rarely voice their dissatisfaction before leaving.
Santander Bank is asking to help them identify dissatisfied customers early in their relationship. Doing so would allow Santander to take proactive steps to improve a customer's happiness before it's too late.
In this machine learning project, you'll work with hundreds of anonymized features to predict if a customer is satisfied or dissatisfied with their banking experience.
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 - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.