Title: APPLIED ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING: PREDICTING AND OPTIMIZING CLICK RATES ON WEB ADVERTISEMENTS #Implementation in Python
Publisher: Our Knowledge Publishing
Publication Date: 2024
Language: English
ISBN 10: 6208195578
ISBN 13: 9786208195571
Binding: Soft cover
Condition: New
Weight: 291 grams

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Synopsis

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.

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