01829nam a22002057a 4500 20240323110553.0 240319b ||||| |||| 00| 0 eng d 9781032395234 AL eng 23 006.3105 CUNM Carlo Requiao da Cunha 155466 Machine learning for the physical sciences : fundamentals and prototyping with julia London CRC Press 2024 xxi,266p. PB 23x14cm. General 7951 ₹5586.28 ₹ ₹7161.90 22% 23/02/2024 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: Ludes 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. computer methods computer information 155467 ddc BK 230532 230532 0 0 ddc 0 0 PHY SACPG SACPG 2024-03-09 Biblios Book Point 5586.28 0 006.3105 CUNM PG024697 2024-03-19 00:00:00 7161.90 2024-03-19 BK