This ebook Linear Algebra and Its Applications with R (PDF) developed from the need to teach a linear algebra course to students focused on data science and bioinformatics programs. These students tend not to realize the importance of linear algebra in applied sciences, since traditional linear algebra courses tend to cover mathematical contexts but not the computational aspect of linear algebra or its applications to data science and bioinformatics.
The author Yoshida presents the topics in a traditional course, yet offers lectures and lab exercises on simulated and empirical data sets. This textbook provides students with a theoretical basis that can then be applied to practical R and Python problems, providing the tools needed for real-world applications.
Each section starts with working examples to demonstrate how tools from linear algebra can help solve problems in applied sciences. These exercises start from easy computations, such as computing determinants of matrices, to practical applications on simulated and empirical data sets with R so that students learn how to get started with R, along with computational examples in each section. Then college students learn how to apply what they’ve learned to problems in applied sciences.
This textbook is designed from first principles to demonstrate the importance of linear algebra through working computational examples with R and Python, including tutorials on how to install R in the Appendix. Students who have never seen R can get started without additional help.
Since Python is one of the most popular languages in data science, optimization, and computer science, code supplements are available for students who feel more comfortable with Python. R is used primarily for computational examples to develop students’ practical computational skills.
978-0367486846, 978-1000400267, 978-1003042259, 978-1032020425
NOTE: This sale only includes the ebook Linear Algebra and Its Applications with R in PDF. No access codes come with the product.
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