Machine Learning: Algorithms, Models, and Applications
Abstract
Recent times are witnessing rapid development in machine learning algorithm systems, especially in reinforcement learning, natural language processing, computer and robot vision, image processing, speech, and emotional processing and understanding. In tune with the increasing importance and relevance of machine learning models, algorithms, and their applications, and with the emergence of more innovative uses cases of deep learning and artificial intelligence, the current volume presents a few innovative research works and their applications in real world, such as stock trading, medical and healthcare systems, and software automation. The chapters in the book illustrate how machine learning and deep learning algorithms and models are designed, optimized, and deployed. The volume will be useful for advanced graduate and doctoral students, researchers, faculty members of universities, practicing data scientists and data engineers, professionals, and consultants working on the broad areas of machine learning, deep learning, and artificial intelligence.
Cite
@article{arxiv.2201.01943,
title = {Machine Learning: Algorithms, Models, and Applications},
author = {Jaydip Sen and Sidra Mehtab and Rajdeep Sen and Abhishek Dutta and Pooja Kherwa and Saheel Ahmed and Pranay Berry and Sahil Khurana and Sonali Singh and David W. W Cadotte and David W. Anderson and Kalum J. Ost and Racheal S. Akinbo and Oladunni A. Daramola and Bongs Lainjo},
journal= {arXiv preprint arXiv:2201.01943},
year = {2022}
}
Comments
Published by IntechOpen, London Uk in Dec 2021. the book contains 6 chapters spanning over 154 pages