
Machine Learning in Mobile Applications
Author(s) -
Veeramani Ganesan
Publication year - 2022
Publication title -
international journal of computer science and mobile computing
Language(s) - English
Resource type - Journals
ISSN - 2320-088X
DOI - 10.47760/ijcsmc.2022.v11i02.013
Subject(s) - computer science , leverage (statistics) , artificial intelligence , machine learning , variety (cybernetics) , mobile device , context (archaeology) , human–computer interaction , data science , world wide web , paleontology , biology
Machine learning is a branch of computer science that enables computers to learn without being explicitly programmed. One of the most exciting technologies that one has ever encountered is machine learning. As the name implies, it provides the computer with the ability to learn, which makes it more human-like. Machine learning is now employed in a variety of applications, including self-driving cars, personal assistants such as Cortana, Alexa, and Siri, and security technologies such as face recognition. Developers of mobile applications are increasingly being pushed to include machine learning technology in their apps. This is unfamiliar territory for many of them. In this research paper, we will look at how machine learning relates to AI in this context, with an emphasis on application developers. This paper demonstrates different machine learning types, frameworks, and tools available on the market and how to use them to create the statistical models needed to use them in mobile applications without having to learn more about the complexity of algorithms and how they train and learn models. Also, this article covers the basic architectures that mobile applications can leverage to work with machine learning.