Popular GitHub Repositories for Telecommunications

Bachelor's thesis carried at Universitat Politecnica de Catalunya in partial fullfilment of the requirements for the degree in Telecommunications Technologies and Services Engineering

Telco Churn Analysis and Modeling is a comprehensive project focused on understanding and predicting customer churn in the telecommunications industry. Utilizing advanced data analysis and machine learning techniques, this project aims to provide insights into customer behavior and help develop effective strategies for customer

Time Series Analyses and Machine Learning for Classifying Events prior to Fiber Cuts

:recycle: :telephone_receiver: Predicting whether a customer will change telecommunications provider and tracking experiments with mlflow

A list of terminologies, and definitions for people who are new to the telecommunications industry.

Neural network approach to adaptive beam forming for future ITS

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an OBJECT DETECTION proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

The goal of this project is to build a machine learning model to predict customer churn for Camtel ?, a major telecommunications provider. Customer churn—the rate at which customers leave the service—is a key challenge that directly impacts revenue ? and business stability ?.

This project creates a user-friendly interface using Gradio to help a telecommunications company manage customer churn, leveraging a machine learning model. Developed in collaboration with the Azubi Africa Data Science Training program.

This repository contains a machine learning-powered web application built using Gradio that predicts customer churn in the telecommunications industry. The app utilizes a pre-trained machine learning model to analyze input features such as customer tenure, monthly charges, and internet services to predict whether a customer is likely to churn or no

This sample API showcases the advantages of using Zuplo on a modular and extensible RESTful API representative of a telecommunications carrier's digital services called Jericalla Mobile.

The project analyzes the phenomenon of customer churn in a telecommunications company using the dataset "Telco Customer Churn".

This repository contains a machine learning-powered web application built using Gradio that predicts customer churn in the telecommunications industry. The app utilizes a pre-trained machine learning model to analyze input features such as customer tenure, monthly charges, and internet services to predict whether a customer is likely to churn or no

Develop a telecommunications customer churn prediction model with different machine learning models

This project focuses on customer churn prediction for a telecommunications company, aiming to identify at-risk customers