Open AccessA Study on Machine Learning: Elements, Characteristics and Algorithms
Author(s) -
K Chokkanathan,
S. Koteeswaran
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.19.13793
Subject(s) - machine learning , computer science , artificial intelligence , field (mathematics) , sample (material) , algorithm , key (lock) , online machine learning , computational learning theory , active learning (machine learning) , mathematics , computer security , chromatography , pure mathematics , chemistry
Machine learning algorithms are used immensely for performing most important computational tasks with the help of sample data sets. Most of the cases Machine learning algorithms will provide best solution where the programming languages failed to produce viable and economically cost-effective results. Huge volume of deterministic problems are addressed and tackled by using the available sample data sets. Because of this now a days machine learning concepts are extensively used in computer science and many other fields. But still we need to explore more to implement machine learning in a specific field such as network analysis, stock trading, spam filters, traffic analysis, real-time and non-real time traffic etc., which may not be available in text books. Here I would like to discourse some of the key points that the machine learning researchers and practitioners can make use of them. These include shortcomings and concerns also.