Knowledge Transactions on

Applied Machine Learning

About the Journal

Almost all the disciplines are integrated and benefited with Machine Learning principles and techniques and invite a platform to exchange the results on theory and practice. There is a strong evidence and expectation to eliminate the gap between theory and experimental approaches. Application and product development can be reported to accelerate the growth qualitatively as well quantitatively.

KtAML is an Open Access Journal. Online readers don't have to pay any fee.

Current Issue

Vol 03. Issue. 01 Jan (2025)
Journal Thumbnail

PUBLISHED: 2025-01-20

Papers

Assessing the Suitability of Ensemble Learning for Consumer Behavior Prediction in NeuromarketingA. Rama,  S. Anusuya  

pp. 1-6

Enhancing ABG Data Prediction: A Comprehensive Comparative Study of Neural Network ArchitecturesS. Ramadoss,  K. Prabhu  

pp. 07-11

Leveraging Usage-Based SaaS Models: Optimizing Revenue and User ExperienceG. Sai Chaitanya Kumar,  B. Dhanalaxmi  

pp. 12-17

Knowledge Transactions on Applied Machine Learning (ktAML) – eISSN: 2972-3817

Indexed in Google Scholar, CrossRef

Plagiarism check  by Turnitin.  Published under CC-BY 4.0.

Planned for Indexing in Elsevier Scopus, Ei Compendex, IET Inspec, EBSCO, DOAJ, dblp and LearnTechLib.