I wonder if he would likely choose Julia now. Julia wasn't around, or it was very early, when he designed the Machine Learning course or was teaching Stanford students, and he's moved on since then. I took the EdX/MIT course on optimization methods and constraint solvers using Julia and JuMP and it was really fun. Most of the features of python that I presented as cons are actually pros when the codebase is more than 1000 lines and needs structure and safety. Also it's nicer to write M * v than np.dot(M,v). After 5 minutes you think you're all set to calculate the M * v, but then your vector happens to be a line vector and not a column vector and you need to learn the difference. In python, you first figure which modules to import, the difference between python arrays and numpy arrays, and god forbid you happen to find the numpy matrix type instead of numpy array type.
In octave you are done in 3 lines of code in 30 seconds. Say, you have some numbers for a matrix and a vector in files and want to read them in and multiple the vector by the matrix. So I guess for newcomers and for quick prototyping (just 10s or 100s lines of code), octave is nicer. The name of the Octave software may at first glance indicate the program and the programming language as a music-related tool, but in fact the Octave is derived from the name of a professor of chemical reaction engineering.In the Stanford/Coursera machine learning class, Andrew Ng said that his teaching experience is that students pick up octave/matlab quicker and the course can cover more actual machine learning, compared to python where more time is spent learning the language. It is accommodated and can be easily expanded and configured by functions defined or user-written functions as well as modules written in C, C ++, Fortran and زبان languages. In addition to a separate component development environment, this programming language is available on VisualStudio and MinGW platforms. Octave software has extensive tools and rich libraries of content needed to solve linear algebra problems, find the roots of nonlinear equations, integrate ordinary functions, manipulate polynomials, integrate differential and differential-algebraic equations, and develop math projects in general.
Gradually, during a series of extensive developments in January 1993, the alpha version was introduced as a flexible tool and a high-level programming language for numerical computing.Īlthough the initial goals of establishing this class-oriented language are somewhat vague, it seems that the designers of this language were more than anything looking for a tool to solve students’ problems in solving problems related to the design of chemical reactors. Of course, at the moment it can be said that Octave is no longer an educational package limited to the classroom. In fact, GNU Octave can be used in a variety of educational, research, and business application applications. Ekerdt of the University of Texas as a free companion software for an undergraduate textbook level in chemical reactor design. Rawlings of the University of Wisconsin-Madison and John G. The Octave language was founded around 1988 by James B. The octave programming language is quite similar to MATLAB software . In such a way that most of the written programs can be transferred to each other by them. In fact, the main purpose of Octave was to provide a high-level language compatible with MATLAB software.
Octave software is used by default through an interactive command line interface. But it can also be used to write non-interactive programs. Octave is a high-level programming language developed primarily for numerical calculations, linear and nonlinear problems, bioinformatics development and mechanical applications, and other digit-related tests. In addition, the service provides you with extensive graphical capabilities for visualizing, visualizing and manipulating data.