Acquaviva, Viviana
Machine Learning for Physics and Astronomy
- ISBN 13:
- 9780691206417
- author:
- Acquaviva, Viviana
- format:
- Paperback
- publisher:
- Princeton University Press
- language:
- English
- Publication Year:
- 2013
- Pages:
- 280
- Dimensions:
- 25.2 x 20.2 x 2.2 centimetres (0
- Genre:
- Science, Mathematical Physics, Science,
- Condition:
- New
- Availability:
- Item usually sent within 10 working days
Description
Machine Learning for Physics and Astronomy provides a hands-on introduction to machine learning and its applications in the physical sciences. As data grows exponentially across these fields, machine learning helps scientists sift through and analyze information, driving advances in quantum physics, astronomy, cosmology, and more.
This textbook covers the basics of building, diagnosing, optimizing, and deploying machine learning methods to solve research problems in physics and astronomy, with a focus on critical thinking and the scientific method. It uses real-world data and examples from cutting-edge research, including identifying galaxy morphology from images and detecting standard model particles in simulations.
Each chapter includes Jupyter Notebook worksheets in Python that enable students to explore key concepts. The book also features review questions and quizzes, making it an ideal resource for advanced undergraduate and early graduate students in STEM disciplines such as physics, computer science, engineering, and applied mathematics.
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