The real world is perceived and broken down as data, models and algorithms in the eyes of physicists and engineers. Data is noisy by nature and classical statistical tools have so far been successful in dealing with relatively smaller levels of randomness. The recent emergence of Big Data and the required computing power to analyse them have rendered classical tools outdated and insufficient. Tools such as random matrix theory and the study of large sample covariance matrices can efficiently process these big data sets and help make sense of modern, deep learning algorithms. Presenting an introductory calculus course for random matrices, the book focusses on modern concepts in matrix theory, generalising the standard concept of probabilistic independence to non-commuting random variables. Concretely worked out examples and applications to financial engineering and portfolio construction make this unique book an essential tool for physicists, engineers, data analysts, and economists.
✔ Author(s): Marc Potters
✔ Title: A First Course in Random Matrix Theory
✔ Rating : 4.1 out of 5 base on (14 reviews)
✔ ISBN-10: 1108488080
✔ ISBN-13: 9781108488082
✔ Language: English
✔ Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
✔ Device compatibles: Android, iOS, PC and Amazon Kindle
Readers' opinions about A First Course in Random Matrix Theory by Marc Potters
Melody Blake
The way the author handled complex emotions and relationships was remarkable. I felt deeply connected to the characters, and their growth throughout the story was both inspiring and moving.
Beata Shepard
The author's ability to evoke a wide range of emotions through their words is truly remarkable. I felt like I was on an emotional rollercoaster throughout the entire book.
Josephine Alvarez
I'm already planning to reread this book. It's one of those stories that you can revisit again and again, discovering new layers of meaning each time.
