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https://github.com/5hraddha/megaline-plan-recommendations

Megaline is a telecom operator and it offers its clients two prepaid plans, Surf and Ultimate.Megaline has found out that many of their subscribers use legacy plans. They want to develop a model that would analyze subscribers' behavior and recommend one of Megaline's newer plans: Smart or Ultra.
https://github.com/5hraddha/megaline-plan-recommendations

decision-tree-classifier logistic-regression random-forest-classifier scikit-learn supervised-learning

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Megaline is a telecom operator and it offers its clients two prepaid plans, Surf and Ultimate.Megaline has found out that many of their subscribers use legacy plans. They want to develop a model that would analyze subscribers' behavior and recommend one of Megaline's newer plans: Smart or Ultra.

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README

        

# Megaline Plan Recommendations to Customers

## Introduction

**Megaline** is a telecom operator and it offers its clients two prepaid plans, **Surf** and **Ultimate**.

**Surf**

- Monthly charge: $20
- 500 monthly minutes, 50 texts, and 15 GB of data
- After exceeding the package limits:
- 1 minute: 3 cents
- 1 text message: 3 cents
- 1 GB of data: $10

**Ultimate**

- Monthly charge: $70
- 3000 monthly minutes, 1000 text messages, and 30 GB of data
- After exceeding the package limits:
- 1 minute: 1 cent
- 1 text message: 1 cent
- 1 GB of data: $7

Megaline has found out that many of their subscribers use legacy plans. **They want to develop a model that would analyze subscribers' behavior and recommend one of Megaline's newer plans: Smart or Ultra**.

## Project Goal

Mobile carrier **Megaline** has found out that many of their subscribers use legacy plans. **They want to develop a model that would analyze subscribers' behavior and recommend one of Megaline's newer plans: Smart or Ultra**.

We need to develop a model with the highest possible accuracy. In this project, the threshold for accuracy is 0.75.