Focusing on engineering and numerical computing, this guide introduces Julia as a powerful tool for data science, machine learning, and scientific applications. It highlights Julia's user-friendly syntax comparable to R, Python, and MATLAB, while offering the performance of C and Java. Readers will explore object-oriented programming principles, basic mathematics, and advanced functionalities, including operations with complex, rational, and irrational numbers, as well as rings and fields.
Solutions for Numerical Computation and Modeling
Focused on hands-on coding, this practical tutorial introduces MATLAB by guiding readers through essential concepts. It begins with the fundamentals and progresses to array-based computing, plotting, file handling, and numerical computation. Key topics include approximations, making it an ideal resource for those looking to grasp MATLAB through direct application and coding exercises.
Open Source Solutions for Numerical Computation
This practical tutorial offers a concise introduction to Python tailored for engineering and scientific computations. Emphasizing hands-on coding, it guides readers through essential concepts, making it an ideal resource for those looking to enhance their programming skills in a technical context.
Familiarize yourself with Octave using this concise, practical tutorial that is focused on writing code to learn concepts.