HDBK OF MACHINE LEARNING (V2): Volume 2: Optimization and Decision Making - Tapa dura

Reseña del editor

Building on Handbook of Machine Learning - Volume 1: Foundation of Artificial Intelligence, this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.

Biografía del autor

Tshilidzi Marwala was born in Venda (Limpopo, South Africa). He is the Vice-Chancellor and Principal of the University of Johannesburg. Previously he was the Deputy Vice-Chancellor for Research and Internationalization and the Executive Dean of the Faculty of Engineering and the Built Environment both at the University of Johannesburg. He holds a Bachelor of Science in Mechanical Engineering (magna cum laude) from Case Western Reserve University (USA) in 1995, a Master of Mechanical Engineering from the University of Pretoria in 1997 and a PhD specializing in Artificial Intelligence and Engineering from the University of Cambridge in 2000. Tshilidzi is a registered professional engineer, a Fellow of TWAS (The World Academy of Sciences), the Academy of Science of South Africa, the African Academy of Sciences and the South African Academy of Engineering. He is a Senior Member of the IEEE (Institute of Electrical and Electronics Engineering) and a distinguished member of the ACM (Association for Computing Machinery). He has received more than 45 awards including the Order of Mapungubwe. His writings and opinions have appeared in the magazines New Scientist, The Economist and Time Magazine.

Collins Achepsah Leke born in Yaounde (Cameroon) is a Post-Doctoral research fellow at the University of Johannesburg. He holds a Bachelor of Science with Honours in Computer Science from University of the Witwatersrand, a Master of Engineering from the University of Johannesburg and PhD in Engineering from the University of Johannesburg. His research interests include the applications of computational intelligence to engineering, computer science, finance, social science and medicine. He has published Deep Learning and Missing Data in Engineering Systems: Applications to Engineering Systems (Springer, 2019).