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MATLAB® for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section I, the reader is introduced to the MATLAB programming language and shown how MATLAB can aid in the understanding of advanced High School Mathematics. In Section II, the reader is shown how MATLAB can be used to solve real-world problems from a broad range of scientific disciplines. The end of Section II introduces Simulink. Finally, in Section III, the reader is introduced to neuron oscillator computing, neural networks, and shown how the Deep Learning Toolbox can be used to solve a large array of problems in Artificial Intelligence (AI).
This book was developed from a series of national and international workshops that the author has been delivering for over twenty-five years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling.
Features:
- No prior experience of programming is required.
- Online GitHub repository available with codes for readers to practice.
- Covers applications and examples from biology, chemistry, computer science, data science, earth sciences, economics, electrical and mechanical engineering, mathematics, physics, psychology, sports science, statistics, and neuron oscillator computing.
- Full solutions to exercises are available on the Web.
Support Material:
GitHub Repository of MATLAB/Simulink files, data files, and Solutions to Exercises:
https://github.com/proflynch/MATLAB-for-Scientific-Computing-and-AI/
MATLAB Central File Exchange:
https://mathworks.com/matlabcentral/profile/authors/63144/
Info autore
Stephen Lynch is a Professor of Digital Skills at Loughborough University, UK. According to the scholarly analytics platform ScholarGPS®, he is currently ranked #13 in the world for Dynamical Systems. He is an author of MapleTM, MATLAB®, Mathematica®, and Python books. In 2022, he was named a National Teaching Fellow, which celebrates and recognises individuals who have made an outstanding impact on student outcomes and teaching in higher education. It is the highest teaching award in the UK. He won the award for his work in programming in the STEM subjects, research feeding into teaching, and widening participation (using experiential and object-based learning). Although educated as a pure mathematician, Stephen's many interests now include applied mathematics, artificial intelligence, cell biology, electrical engineering, computing, neural networks, nonlinear optics, and binary oscillator computing, which he co-invented with a colleague. He has authored 2 international patents for inventions, 11 books, 4 book chapters, over 50 journal articles, and a few conference proceedings. Stephen is a Fellow of the Institute of Mathematics and Its Applications (FIMA) and a Senior Fellow of the Higher Education Academy (SFHEA). In 2010, Stephen volunteered as a STEM Ambassador, in 2012, he was awarded Public Engagement Champion status, and in 2014 he became a Speaker for Schools. He runs national workshops on "Python for A-Level Mathematics and Beyond," and international workshops on "Python for Scientific Computing and TensorFlow for Artificial Intelligence." He has run workshops in China, Malaysia, Saudi Arabia, Singapore, and the USA.
