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Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.

Telecom Customer Churn Analysis

By: Quantiphi Latest Version: 1.0

Product Overview

This algorithm helps in predicting the possibilty of churn in telecom industry using Random Forest binary classifier from scikit-learn library. It uses the SMOTE function from imblearn library to overcome the class imbalance and uses recall score as metric for determining the quality of the model. Input data should be given in a csv format. This algorithm supports hyperparameter tuning to tune your model as per the requirement

Key Data

By Quantiphi
Type Algorithm
Fulfillment Methods Amazon SageMaker

Usage Information

Fulfillment Methods

Amazon SageMaker

Support Information

AWS Infrastructure

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This product is offered for free. If there are any questions, please contact us for further clarifications.

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