Showing results for Telecom Product Product
GitHub Repo
https://github.com/09varshachoudhary-beep/telecom-productService
09varshachoudhary-beep/telecom-productService
No repository description available.
GitHub Repo
https://github.com/AbidaMehnaz/Recommender_System_for_Telecom_Services
AbidaMehnaz/Recommender_System_for_Telecom_Services
Product/ Service recommendations for telecom
GitHub Repo
https://github.com/sajansshergill/product-experimentation-platform
sajansshergill/product-experimentation-platform
Telecom Product Analytics & Experimentation Platform
GitHub Repo
https://github.com/SamiraSamrose/astra_grid_production
SamiraSamrose/astra_grid_production
Autonomous Telecom & Data Center Guardian
GitHub Repo
https://github.com/leithmajdoub/TelecomProductivityToolFront
leithmajdoub/TelecomProductivityToolFront
No repository description available.
GitHub Repo
https://github.com/himajakinthada28/TelecommunicationChurnAnalysisPrediction
himajakinthada28/TelecommunicationChurnAnalysisPrediction
As the regular day-to-day activities are completely subjected to the utilization of telecom products and its services, the global market for telecommunication is escalated to grow at a phenomenal rate over the coming years. It is more important for the telecom industries to save their customers. The officials of the telecom industry must find their ways to improve the customer strength while maintaining the current customer rate and also retaining back old customers. The process where one customer leaves one company and joins another is called as churn. Churn is a very important area in which the telecom domain can make or lose their customers and hence the business/industry spends a lot of time doing predictions, which in turn helps to make the necessary business conclusions. Churn can be avoided by studying the past history of customers. The powerful weapon in today’s telecom industry is keeping the existence customers and acquiring new customers. Since the churn customers are increasing which brings the domains experts in action to make necessary churn analysis of customers. Churn prediction can be implemented through various supervised machine learning models. The company introduces new techniques and applications to increase the services to retain the customers. Various telecom companies are coming with advanced tactics in order to predict the churned customer in early stage. Traditionally, various types of machine learning approaches like Decision tree, Random Forest, and Bagging etc., were applied to predict churned customer. According the literature survey, the churn predictions for telecom industries also uses deep learning techniques for better accuracy and low processing time.
GitHub Repo
https://github.com/RaniRupam/product-service
RaniRupam/product-service
Spring Boot Product Service for Telecom Project
GitHub Repo
https://github.com/Star2Billing/a2billing
Star2Billing/a2billing
A2Billing is a telecom switch and billing system capable of providing and billing a range of telecom products and services to customers such as calling card products, residential and wholesale VoIP termination, DID resale and callback services.
GitHub Repo
https://github.com/Trabelsibahe/telecom
Trabelsibahe/telecom
An e-shop that sells Tunisie Telecom products.
GitHub Repo
https://github.com/leithmajdoub/TelecomProductivityTool