Advances in Machine Learning and Deep Learning Algorithms and Their Applications

Abstract

In this work, machine learning and deep learning algorithms are explained with examples. The relationship between machine learning, deep learning and artificial intelligence is also detailed out. Applications of machine learning and deep learning are listed. Difference between machine learning and deep learning is explained in various dimensions of size of data, hardware, applications, type of prediction, number of layers, etc. Machine learning algorithms are classified into three main groups, namely supervised learning methods, unsupervised learning methods, and reinforcement leaning methods. Some of the supervised learning techniques like linear regression, logistic regression, naive Bayes, and support vector machines are explained in brief. Unsupervised learning techniques like principal component analysis and linear discriminant analysis are also explained. Deep learning algorithms have been detailed out, and examples are given.