Description: Machine Learning for Physics and Astronomy, Paperback by Acquaviva, Viviana, ISBN 0691206414, ISBN-13 9780691206417, Like New Used, Free shipping in the US "A hands-on introduction to machine learning and its applications to the physical sciences. As the size and complexity of data continue to grow exponentially across the physical sciences, machine learning is helping scientists to sift through and analyzethis information while driving breathtaking advances in quantum physics, astronomy, cosmology, and beyond. This incisive textbook covers the basics of building, diagnosing, optimizing, and deploying machine learning methods to solve research problems in physics and astronomy, with an emphasis on critical thinking and the scientific method. Using a hands-on approach to learning, Machine Learning for Physics and Astronomy draws on real-world, publicly available data as well as examples taken directly from the frontiers of research, from identifying galaxy morphology from images to identifying the signature of standard model particles in simulations at the Large Hadron Collider. Introduces readers to best practices in data-driven problem-solving, from preliminary data exploration and cleaning to selecting the best method for a given task. Each chapter is accompanied by Jupyter Not worksheets in Python that enable students to explore key conceptsIncludes a wealth of review questions and quizzesIdeal foradvanced undergraduate and early graduate students in STEM disciplines such as physics, computer science, engineering, and applied mathematics. Accessible to self-learners with a basic knowledge of linear algebra and calculus. Slides and assessment questions (available only to instructors)"--
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End Time: 2024-08-05T02:48:21.000Z
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Book Title: Machine Learning for Physics and Astronomy
Number of Pages: 280 Pages
Language: English
Publisher: Princeton University Press
Publication Year: 2023
Topic: Physics / Astrophysics, Physics / Mathematical & Computational, Astronomy
Item Height: 0.7 in
Illustrator: Yes
Genre: Science
Item Weight: 24.1 Oz
Author: Viviana Acquaviva
Item Length: 10 in
Item Width: 8 in
Format: Trade Paperback