If you’re a student focused on data science or bioinformatics programs, then you might not have realized the importance of linear algebra in applied sciences. Linear Algebra and Its Applications with R (PDF) is an ebook that has been created to fulfill the need of teaching linear algebra courses to data science and bioinformatics students. It offers lectures and lab exercises on simulated and empirical data sets, and introduces students to the theoretical basis, which can be applied to practical R and Python problems for real-world applications.
The textbook has been designed in a way that ensures that no prior knowledge of R is required; it presents the topics in a traditional way, followed by working examples to demonstrate how tools from linear algebra can help solve problems in applied sciences. These exercises range from easy computations, such as computing determinants of matrices, to practical applications on simulated and empirical data sets with R, ensuring that students learn how to get started with R along with computational examples in every section.
This ebook is a comprehensive guide to understanding linear algebra’s computational aspect and its applications to data science, bioinformatics, and other applied sciences. The author, Yoshida, has presented the course material with clarity, and the code supplements available for Python ensure that this textbook can be used by students who prefer coding in Python as well. Since Python is one of the most popular languages in data science, optimization, and computer science, it will give students a better edge.
If you’re interested in purchasing this ebook, please note that this sale only includes the ebook Linear Algebra and Its Applications with R in PDF format and no access codes come with the product. For those who have never seen R, tutorials on how to install R are included in the ebook. Don’t miss out on this incredible resource for learning linear algebra with R.
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