Practical Linear Algebra for Data Science - From Core Concepts to Applications Using Python

"If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way it's presented in decades-old textbooks is much different from how professionals use linear algebra today to solve real-world modern applications. This practical guide from Mike X Cohen teaches the core concepts of linear algebra as implemented in Python, including how they're used in data science, machine learning, deep learning, computational simulations, and biomedical data processing applications. Armed with knowledge from this book, you'll be able to understand, implement, and adapt myriad modern analysis methods and algorithms."--Publisher marketing.

About the author

Mike is an associate professor of neuroscience at the Donders Institute (Radboud University Medical Centre) in the Netherlands. He has over 20 years experience teaching scientific coding, data analysis, statistics, and related topics, and has authored several online courses and textbooks. He has a suspiciously dry sense of humor and enjoys anything purple.

Product details

• Authors: Mike Cohen, Mike X. Cohen, Mike X Cohen
• Publisher: O'Reilly
• Languages: English
• Product format: Paperback / Softback
• Released: 30.11.2022
• EAN: 9781098120610
• ISBN: 978-1-09-812061-0
• Dimensions: 178 mm x 233 mm x 18 mm
• Weight: 564 g
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; machine learning, COMPUTERS / Data Science / Machine Learning