Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Fundamental Mathematical Concepts for Machine Learning in Science

Fundamental Mathematical Concepts for Machine Learning in Science

Michelucci, Umberto

Hardcover

Anatomy & PhysiologyGeneral ComputersPhysics

Currently unavailable to order

ISBN10: 3031564308
ISBN13: 9783031564307
Publisher: Springer
Published: May 17 2024
Pages: 249
Weight: 1.20
Height: 0.80 Width: 6.30 Depth: 9.20
Language: English

This book is for individuals with a scientific background who aspire to apply machine learning within various natural science disciplines--such as physics, chemistry, biology, medicine, psychology and many more. It elucidates core mathematical concepts in an accessible and straightforward manner, maintaining rigorous mathematical integrity. For readers more versed in mathematics, the book includes advanced sections that are not prerequisites for the initial reading. It ensures concepts are clearly defined and theorems are proven where it's pertinent. Machine learning transcends the mere implementation and training of algorithms; it encompasses the broader challenges of constructing robust datasets, model validation, addressing imbalanced datasets, and fine-tuning hyperparameters. These topics are thoroughly examined within the text, along with the theoretical foundations underlying these methods. Rather than concentrating on particular algorithms this book focuses on the comprehensive concepts and theories essential for their application. It stands as an indispensable resource for any scientist keen on integrating machine learning effectively into their research.

Also from

Michelucci, Umberto

View All

Also in

General Computers

View All