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Machine Learning for the Physical Sciences

- Fundamentals and Prototyping with Julia
Af: Carlo Requiao da Cunha Engelsk Paperback

Machine Learning for the Physical Sciences

- Fundamentals and Prototyping with Julia
Af: Carlo Requiao da Cunha Engelsk Paperback
Tjek vores konkurrenters priser

Machine learning is an exciting topic with a myriad of applications. However, most textbooks are targeted towards computer science students. This, however, creates a complication for scientists across the physical sciences that also want to understand the main concepts of machine learning and look ahead to applica- tions and advancements in their fields.

This textbook bridges this gap, providing an introduction to the mathematical foundations for the main algorithms used in machine learning for those from the physical sciences, without a formal background in computer science. It demon- strates how machine learning can be used to solve problems in physics and engineering, targeting senior undergraduate and graduate students in physics and electrical engineering, alongside advanced researchers.

All codes are available on the author''s website: C•Lab (nau.edu)

They are also available on GitHub: https://github.com/StxGuy/MachineLearning

Key Features:

  • Includes detailed algorithms.
  • Supplemented by codes in Julia: a high-performing language and one that is easy to read for those in the natural sciences.
  • All algorithms are presented with a good mathematical background.
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Tjek vores konkurrenters priser
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Tjek vores konkurrenters priser

Machine learning is an exciting topic with a myriad of applications. However, most textbooks are targeted towards computer science students. This, however, creates a complication for scientists across the physical sciences that also want to understand the main concepts of machine learning and look ahead to applica- tions and advancements in their fields.

This textbook bridges this gap, providing an introduction to the mathematical foundations for the main algorithms used in machine learning for those from the physical sciences, without a formal background in computer science. It demon- strates how machine learning can be used to solve problems in physics and engineering, targeting senior undergraduate and graduate students in physics and electrical engineering, alongside advanced researchers.

All codes are available on the author''s website: C•Lab (nau.edu)

They are also available on GitHub: https://github.com/StxGuy/MachineLearning

Key Features:

  • Includes detailed algorithms.
  • Supplemented by codes in Julia: a high-performing language and one that is easy to read for those in the natural sciences.
  • All algorithms are presented with a good mathematical background.
Vis mere
Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 266
ISBN-13: 9781032395234
Indbinding: Paperback
Udgave:
ISBN-10: 1032395230
Kategori: Automatisk styrings- & reguleringsteknik
Udg. Dato: 11 dec 2023
Længde: 21mm
Bredde: 234mm
Højde: 155mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 11 dec 2023
Forfatter(e): Carlo Requiao da Cunha
Forfatter(e) Carlo Requiao da Cunha

Kategori Automatisk styrings- & reguleringsteknik

ISBN-13 9781032395234

Sprog Engelsk

Indbinding Paperback

Sider 266

Udgave

Længde 21mm

Bredde 234mm

Højde 155mm

Udg. Dato 11 dec 2023

Oplagsdato 11 dec 2023

Forlag Taylor & Francis Ltd