A School of Artificial Intelligence with Machine Learning Theoretical Aspects and PYTHON Applications

Machine learning, which is expressed as a sub-field of artificial intelligence; It is widely used in many fields led by engineering, finance and bioinformatics. In order to develop machine learning applications, it is important to understand some algorithms that contain calculus, linear algebra and statistics theoretically. After learning the theoretical aspects of these algorithms, an application can be developed by coding it with a programming language with an easy and rich library structure such as Python. The theoretical aspects of machine learning algorithms in the book were meticulously examined, and the necessary linear algebra and statistics were also briefly examined. Python applications were developed for each algorithm using problems containing original datasets. People who want to develop applications with Deep Learning, which is a sub-field of machine learning, especially learn the basic information in this book, will provide an important infrastructure. Deep learning architectures will be easier to understand after reading this book.
Who is this book for?
• Those who want to start developing a Machine Learning application but do not know exactly where to start,
• Those who are already developing Machine Learning applications,
• Those who prepare dissertations involving Machine Learning and conduct scientific studies in the fields of Science, Engineering and Social Sciences