A Teacher from Dept. of Computer Science Issues A Book On Machine Learning Methods & Algorithms

Prof. Dr. Ahmed Tariq Sadiq, a lecturer in Computer Science Dept. at UOT , published his new book "Methods and Algorithms for Machine Learning", published by Dar Al-Thakira.

The book consists of 10 chapters dealing with a number of methods and algorithms of artificial intelligence and machine learning, where the subject of machine learning is one of the most important topics of artificial intelligence, and it includes a wide range of applications of artificial intelligence. If there were no methods and algorithms of machine learning, artificial intelligence would have been late and not amounted to artificial intelligence. 

 The author stated, "Given the importance of the subject of machine learning in all modern sciences in general and computer science in particular, we have decided that our fluent Arabic language should have a share in clarifying and explaining the methods and algorithms of this important topic in  present time and for  next years" 

He pointed out that the book includes a scientific and systematic explanation of the methods and algorithms for learning the machine from its beginnings until now. The first chapter dealt with introductions to the subject of machine learning and its history, the most important terms for machine learning, methods of selecting characteristics and criteria for evaluating the performance of machine learning methods and algorithms. 

He added that the second chapter dealt with learning the statistical machine and its methods such as linear regression, logical regression, linear discriminant analysis, principal component analysis, and the nearest neighbor algorithm. While the third chapter dealt with decision tree algorithms of various kinds that played an important role in machine learning from the beginning to the present day, while the fourth chapter dealt with approximate group theory, which is one of the most important methods of machine learning inspired by group theory. 

He mentioned that the fifth chapter contains the algorithms of artificial neural networks that have made a quantum leap in the subject of machine learning, and also includes seven important algorithms from the algorithms of artificial neural networks. The sixth chapter contains the concepts and principles of genetic algorithms and what is related to them, which is one of the most important methods of implicit machine learning.

The seventh chapter dealt with the vector support machine method, which is considered one of the most important mathematical and algebraic methods in the subject of machine learning. The eighth chapter dealt with the method of Bayes networks in relation to the mathematical statistician Bayes, who had a great merit in the development of statistics, leading to the benefit of his method of learning the machine. As for the reinforcement learning that has recently developed remarkably, it has its share of this book in the ninth chapter specifically.

The final chapter dealt with deep machine learning and the two most important methods are bypass neural networks and recurrent neural networks.