Implementations and Applications of Machine Learning

Saad Subair was born on the banks of the river Nile, a few kilometers away from the capital Khartoum He is a Professor of Bioinformatics and Computer Science at the College of Computer Studies, International University of Africa (IUA), Khartoum, Sudan. Prof. Subair obtained a BSc from the University of Khartoum, PGD, MSc (Computer Science) and PhD (Bioinformatics) from UTM, Malaysia, and an MSc in Genetics from UPM, Malaysia He is an author and/or contributing author to several books, articles, and scientific papers published in USA, Germany, Malaysia, India, and Arabia. He has been Keynote Speaker in numerous regional conferences. Prof. Subair is a member of scientific and academic committees in multiple universities in the Gulf region including Princess Nourah bint Abdulrahman University at Riyadh, KSA. Prof Subair has trained hundreds of students in the fields of machine learning and bioinformatics, and has supervised and/or advised several research students who have achieved further successes in the UK and USA.

Introduction.- Part 1: Machine learning concepts, methods, and software tools.- Overview.- Classifying algorithms.- Support vector machines.- Bayes classifiers.- Decision trees.- Clustering algorithms.- k-means and variants.- Gaussian mixture.- Association rules.- Optimization algorithms.- Genetic algorithms.- Swarm intelligence.- Deep learning,- Convolutional neural networks (CNN).- Other deep learning schema.- Part 2: Applications with implementations.- Protein secondary structure prediction.- Mapping heart disease risk.- Surgical performance monitoring.- Power grid control.- Conclusion.