Bilal SGUIRI, Faiq GMIRA, Salwa HABIBY

APPLIED ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

PREDICTING AND OPTIMIZING CLICK RATES ON WEB ADVERTISEMENTS #Implementation in Python

• Broschiertes Buch

Produktbeschreibung

The click-through rate on web ads measures the number of clicks they receive from all customers who view them from web browsers.This paper, with the aim of anticipating customer preferences, proposes an approach that uses AI and ML to design and implement hyper-personalized experiences to automate the complex tasks related to predicting customer behaviors to better understand them and offer them intelligent web advertising.The proposed approach is based on granular customer segmentation, dynamic content adaptation, precise product recommendations and predictive analysis. To implement cognitive functions, data comes from Chatbots processed with data analysis, multivariate testing, attribution modeling and predictive optimization.A case study is discussed and the solution proposed and programmed with the Python language and its machine learning libraries: Pandas, NumPy, Matplotlib and Scikit-learn.

Produktdetails

• Verlag: Our Knowledge Publishing
• Seitenzahl: 108
• Erscheinungstermin: 17. Oktober 2024
• Englisch
• Abmessung: 220mm x 150mm x 7mm
• Gewicht: 179g
• ISBN-13: 9786208195571
• ISBN-10: 6208195578
• Artikelnr.: 71926723

Autorenporträt

Bilal SGUIRI è un giovane ricercatore interessato all'informatica in generale e all'intelligenza artificiale e all'apprendimento automatico in particolare. La sua ricerca si concentra sullo sviluppo di algoritmi per macchine in grado di simulare i processi cognitivi umani per consentire loro di imparare e migliorare da sole.