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Back to Machine Learning for Telecom Customers Churn Prediction

Learner Reviews & Feedback for Machine Learning for Telecom Customers Churn Prediction by Coursera Project Network

4.6
stars
36 ratings

About the Course

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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1 - 5 of 5 Reviews for Machine Learning for Telecom Customers Churn Prediction

By Vinoth S U

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Jul 13, 2021

Great path to learn ML Algorithm

By Marco T

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Apr 12, 2021

Course was good and clear

By Juan E Z

•

Jun 23, 2023

Super useful!

By Darshan K

•

Jul 13, 2023

good

By Pompilia B

•

Jun 4, 2024

The instructor only explains how to do things, not why to do them in that way and not another way. This is not proper teaching, it is merely instructing. The explanation of the various algorithms involved is based on other examples that have nothing to do with customer churn prediction. The interpretation of the results doesn't really exist in a way that a person without a ML background would understand. I was kicked out of the workspace environment because I used it too much, apparently - I did not know beforehand that that was a thing, I just woke up one day to see I cannot use it anymore. I find this unacceptable for a project that one pays for. I completed this guided project on a Coursera premium free trial and they won't let me download my certificate until my trial ends and payment is processed. They could have been transparent about this before investing time in the project but I guess Coursera is too stingy to also be honest and transparent. Well, I guess there won't be any paid membership in this case. ;-)