Advanced Topics in Machine Learning

Author:

Zeba Sana1,Alimul Haque Md.2,Alhazmi Samah3,Shameemul Haque 4

Affiliation:

1. Jamia Millia Islamia University,Department of Computer Engineering,New Delhi, India

2. Veer Kunwar Singh University,Department of Computer Science,Ara, India

3. College of Computing and Informatics, Saudi Electronic University,Riyadh,Saudi Arabia

4. Al-Hafeez College,Ara, India

Abstract

This chapter reveals the infancy of the striking experience near the “Internet of Things (IoT)”. Machine learning technology is a part of Artificial Intelligence that grew from the training of computational learning approaches and pattern recognition of artificial intelligence. Over the last few years, Machine Learning approaches have been advanced inquisitively for various sectors such as smart city, finance, banking, education, etc. Today machine learning is not similar to the previous machine learning because of various new advanced computing techniques. Machine learning technique is defined as data analysis that automates the building of analytical models. The iterative factor of learning algorithms is significant as models are uncovered to new datasets; they are skilled in autonomously adjusting. The study from earlier computations generates reliable, efficient, repeatable decisions and experiment results. Therefore, Machine Learning measures have been used to protect various smart applications from any illegal activities, threats, and various attacks. Furthermore, Machine Learning provided suitable solutions for preserving the security of various advanced applications. The patent growth rate is 34% in the machine learning field from the year 2013 to 2017, according to Patent Service IFI Claims. Also, in the world, 60% of companies are using various learning algorithms for numerous purposes. In this chapter, we have discussed efficient, advanced, and revolutionary machine learning algorithms in detail.

Publisher

BENTHAM SCIENCE PUBLISHERS

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