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Machine Learning for Telecom Customers Churn Prediction

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In this hands-on project, we will train several classification algorithms such as Logistic Regression, Support Vector Machine, K-Nearest Neighbors, and Random Forest Classifier to predict the churn rate of Telecommunication Customers. Machine learning help companies analyze customer churn rate based on several factors such as services subscribed by customers, tenure rate, and payment method. Predicting churn rate is crucial for these companies because the cost of retaining an existing customer is far less than acquiring a new one. Note: This course works best for learners who are based in the North America region. We're currently working on providing the same experience in other regions.

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This beginner-friendly course, "Machine Learning for Telecom Customers Churn Prediction," focuses on using classification algorithms to predict telecom customer churn. Offered by Coursera, it covers Logistic Regression, Support Vector Machine, K-Nearest Neighbors, and Random Forest Classifier. The course is hands-on, lasts 180 minutes, and is free, targeting IT and Computer Science enthusiasts, especially in North America.