ResearchBib Share Your Research, Maximize Your Social Impacts
Sign for Notice Everyday Sign up >> Login

Traditional Machine Learning and No Code Machine Learning with its Features and Application

Journal: International Journal of Trend in Scientific Research and Development (Vol.5, No. 2)

Publication Date:

Authors : ;

Page : 29-32

Keywords : Auto-Code Generation; Deep Learning; Artificial Intelligent; Auto algorithm selection; No-Code ML platforms;

Source : Downloadexternal Find it from : Google Scholarexternal

Abstract

This is the new era of technology development where all the things and work is done by the machines. The goal of Information Technology is to develop a device which is able to work like a human itself. For that Artificial Intelligence, Machine Learning and Deep Learning are going to be used. Machine Learning is a subpart of the Artificial Intelligent which helps a machine to learn by itself. To apply learning processes on machines it required deep knowledge of programming, mathematics and statistics. Now it is not a big problem, as the technology is changing day by day the new concept known as No Code ML and Auto Code Generation are introduced. This helps the users to create a model without doing any kind of coding. In this new technology everyone is able to create a model and use machine learning. There are several platforms which provide this kind of facilities. The models created on those platforms give good accuracy and desire outcomes as well. Hiteshkumar Babubhai Vora | Hardik Anilbhai Mirani | Vraj Bhatt "Traditional Machine Learning and No-Code Machine Learning with its Features and Application" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38287.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/38287/traditional-machine-learning-and-nocode-machine-learning-with-its-features-and-application/hiteshkumar-babubhai-vora

Last modified: 2021-04-09 15:55:09