Numerical Methods for Engineering and Data by Rolf Wuthrich (.ePUB)+

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File Size: 43.5 MB

Numerical Methods for Engineering and Data Science by Rolf Wuthrich, Carole El Ayoubi
Requirements: .ePUB, .PDF reader, 43.5 MB
Overview: Numerical Methods for Engineering and Data Science guides students in implementing numerical methods in engineering and in assessing their limitations and accuracy, particularly using algorithms from the field of Machine Learning. The textbook presents key principles building upon the fundamentals of engineering mathematics. It explores classical techniques for solving linear and nonlinear equations, computing definite integrals and differential equations. Emphasis is placed on the theoretical underpinnings, with an in-depth discussion of the sources of errors, and in the practical implementation of these using Octave. Each chapter is supplemented with examples and exercises designed to reinforce the concepts and encourage hands-on practice. The second half of the book transitions into the realm of Machine Learning. The authors introduce basic concepts and algorithms, such as linear regression and classification. In the present book, we use Octave for the first part, and the Python library SciKit Learn in the second part.
Genre: Non-Fiction > Tech & Devices

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