The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Application of Machine Learning for Software Engineers
|
|
Author(s): Sunil Kumar Rajak (G.L. Bajaj Institute of Technology and Management, India), Shabanam Kumari (G.L. Bajaj Institute of Technology and Management, India), Mohit Kumar (G.L. Bajaj Institute of Technology and Management, India)and Dhirendra Siddharth (G.L. Bajaj Institute of Technology and Management, India)
Copyright: 2024
Pages: 16
Source title:
Advancing Software Engineering Through AI, Federated Learning, and Large Language Models
Source Author(s)/Editor(s): Avinash Kumar Sharma (Sharda University, India), Nitin Chanderwal (University of Cincinnati, USA), Amarjeet Prajapati (Jaypee Institute of Information Technology, India), Pancham Singh (Ajay Kumar Garg Engineering College, Ghaziabad, India)and Mrignainy Kansal (Netaji Subhas University of Technology (NSUT), Delhi, India)
DOI: 10.4018/979-8-3693-3502-4.ch004
Purchase
|
Abstract
Machine learning is becoming increasingly popular in software engineering due of its capabilities. By studying and learning from data using algorithms, software systems may improve their performance and adapt to new conditions without having to explicitly programme. Software engineers may use machine learning to build systems that learn and adapt over time, resulting in more effective and efficient issue solutions. Software engineering uses machine learning in a variety of ways, such as recommendation systems, natural language processing, video and image analysis, and predictive modelling. Machine learning is likely to have a significant impact on how software is built and used across industries as it becomes more widely used. The application of machine learning in software engineering has the potential to transform how software systems are created and utilised. Machine learning allows systems to learn and adapt to changing data and settings, resulting in more efficient and effective solutions to a variety of problems.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|