Copertina

Predicting the Success of Marketing Campaigns in the Banking Sector

Fuente: Zenodo

Salvato in:

Dettagli Bibliografici
Autore principale:	Harshith P
Natura:	Recurso digital
Lingua:	inglese
Pubblicazione:	Zenodo 2025
Soggetti:	Marketing Campaigns, Machine Learning, Banking Sector, Random Forest, Predictive Analytics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Student Performance Prediction Using Machine Learning
di: Hrutuja Umakant Aher
Pubblicazione: (2026)

Customer Churn Prediction in the Software by Subscription models IT business using machine learning methods
di: Kolesnikova, Kateryna
Pubblicazione: (2021)

Machine Learning-Based Employee Performance Rating System
di: Siddharth Sharma, et al.
Pubblicazione: (2026)

"eHealth Informatics using EHR: A Comparative Analysis of Data Mining Classification Techniques"
di: Dr. Vaishali S Parsania
Pubblicazione: (2023)

IgniWise Dataset — Prescribed Burn Window Prediction for Spain (1983–2015)
di: Romera Martínez, Sergio
Pubblicazione: (2026)

Artificial Intelligence in Marketing and Distribution: A Review of Concepts, Applications and Impacts
di: Bagal, Ranjana Rahul
Pubblicazione: (2026)

AI in Traffic Management Predicting, Congestion Patterns and Optimization Signal Timing in Mega Urban Project
di: Amarsinh B. Landage, et al.
Pubblicazione: (2026)

AI-DRIVEN CREDIT RISK ASSESSMENT IN BANKING AT ICICI BANK
di: Journal of Digital Engineering and Business Management
Pubblicazione: (2026)

Artificial Intelligence for Business Growth Through Marketing: A Technical Perspective
di: Vishal Uttam Mane
Pubblicazione: (2026)

Leveraging AI for Predictive Consumer Insights in Green Product Marketing: A Case of North Karnataka MSMEs
di: Salunke, Shital
Pubblicazione: (2026)

EVALUATING FEATURE SELECTION METHODS AND CLASSIFIERS FOR CROP PREDICTION
di: International Journal of Technology, Leadership and Sciences
Pubblicazione: (2026)

INTELLIGUARD: ENHANCED SOFTWARE DEFECT FORECASTING WITH ML
di: DIVIDEVARA SAI TEJA , G. PRAVEEN BABU
Pubblicazione: (2025)

Insights into breast cancer: A simple machine learning method for early disease detection
di: Sowah, Anthony, et al.
Pubblicazione: (2025)

A Machine Learning Framework for Personalized Job Recommendation
di: Rumana Hasinullah Shaikh, et al.
Pubblicazione: (2026)

AI software for personalized marketing automation in SMEs: Enhancing customer experience and sales
di: Wagobera Edgar Kedi, et al.
Pubblicazione: (2024)

Chapter Ammonia emissions and fine particulate matter: some evidence in Lombardy
di: Salis, Matteo, et al.
Pubblicazione: (2023)

Integrating machine learning and prioritization to decipher the partitioning and risk of tire-derived chemicals in highly populated coastal regions.
di: Wu, Nian-Nian, et al.
Pubblicazione: (2026)

Big Data Cloud Computing and AI-Driven Digital Marketing in Enterprise Systems
di: Yosra, Ali Hassan, et al.
Pubblicazione: (2025)

AI-Enabled Smart Career Trajectory Mapping, Predictive Analytics, and Skill Recommendation Platform
di: Venkatesh S, et al.
Pubblicazione: (2026)

Application of bayesian additive regression trees in the development of credit scoring models in Brazil
di: Daniel Alves de Brito
Pubblicazione: (2018)

Crop Advisor: Intelligent Crop Recommendation System
di: Viraj Nalawade
Pubblicazione: (2025)

IMPROVING THE RELIABILITY OF MACHINE LEARNING MODELS BY FILLING IN MISSING NAN VALUES IN MEDICAL DATASETS USING A GENETIC ALGORITHM
di: Shokhrukh Sariyev
Pubblicazione: (2025)

Diseño de un modelo de detección temprana de amenazas cibernéticas en PYMES colombianas mediante técnicas de inteligencia artificial
di: Reina, Edgar Andres
Pubblicazione: (2026)

Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
di: Mauricio Castro Franco
Pubblicazione: (2017)

Application of Different Machine Learning Techniques for Predicting Heart Dieses
di: Tejaswini Zope, et al.
Pubblicazione: (2021)

Chapter Supporting decision-makers in healthcare domain. A comparative study of two interpretative proposals for Random Forests
di: Aria, Massimo, et al.
Pubblicazione: (2022)

Comparative Analysis of ML Models with Selection Methods for Early Predictive Analytics of Sepsis in ICU
di: Vandana, et al.
Pubblicazione: (2024)

Hierarchical pattern recognition in milking parameters predicts mastitis prevalence
di: Ebrahimie, Esmaeil, et al.
Pubblicazione: (2018)

Data Driven Attrition Prediction In Enterprise Organization
di: Rozina Naz, et al.
Pubblicazione: (2026)

Predictive Analytics: A study of its Advantages and Applications
di: Mitanshi Rustagi
Pubblicazione: (2022)

DETERMINANTS OF DEPOSIT MOBILIZATION OF COMMERCIAL BANKS: THE STUDY ON SELECTED PRIVATE COMMERCIAL BANKS IN ETHIOPIA
di: CHALI FAYERA, et al.
Pubblicazione: (2025)

Integration of AI into CRM for Effective U.S. healthcare and pharmaceutical marketing
di: Unanah, Onyekachukwu Victor, et al.
Pubblicazione: (2025)

Aplicación de una red neuronal feed-forward backpropagation para el diagnóstico de fallas mecánicas en motores de encendido provocado
di: Wilmer Contreras Urgilés
Pubblicazione: (2019)

PALSAR-2/ALOS-2 AND OLI/LANDSAT-8 DATA INTEGRATION FOR LAND USE AND LAND COVER MAPPING IN NORTHERN BRAZILIAN AMAZON
di: João Arthur Pompeu Pavanelli
Pubblicazione: (2018)

AI-Driven Workforce Productivity Optimization in U.S. Service Organizations Using KPI-Based Predictive Analytics
di: Akter, Tahamina
Pubblicazione: (2026)

Enhancing Marble Waste Recycling Through Machine Learning: The Role of Particle Size Variation and Class Imbalance Mitigation
di: Shambhavi Sinha
Pubblicazione: (2026)

Aplicación de algoritmos Random Forest y XGBoost en una base de solicitudes de tarjetas de crédito
di: Javier Jesús Espinosa-Zúñiga
Pubblicazione: (2020)

Estimación de volumen forestal mediante imágenes de satélite Landsat 8 OLI en bosques templados mixtos
di: Pedro García-Ramírez
Pubblicazione: (2020)

Intelligent cloud automation: Leveraging AI and machine learning for enhanced cloud management
di: Kata, Venkatesh
Pubblicazione: (2025)

Predictive Crop Yield Modeling and Soil Quality Classification using Machine Learning
di: Manju Sadasivan, et al.
Pubblicazione: (2025)