MATLAB

"Modelamiento matemático"

Comentarios: En ciertos momentos de mis estudios universitarios, ha sido necesario realizar ciertas pruebas, para analizar sus modelos matemáticos, pero aplicados de manera empírica.

Puntos a favor: Presenta una manera muy simple de trabajar con el lenguaje para trabajar con arreglos o vectores, utilizar funciones donde operen estos, y graficar resultados. Además de que tiene una muy buena documentación, con ejemplos claros.

Contras: Utilizar o instalar ciertos paquetes, no me ha resultado cómodo cuando he tenido que descargar e instalarlos.

"Amazing tool once you get to know it"

Comentarios: I administer this at work and use it personally. So far it has been great

Puntos a favor: So many features! This tool can do anything once you learn how to use it. I recommend some sort of class to teach you how to use it

Contras: severe learning curve especially if you haven't used any modeling software ever. Can be a bit intimidating at first

"The Harbinger of Engineering Research"

Comentarios: MATLAB has been at the centerstage of our academic activities in general and research in particular. It has helped in solving research problems in the area of image processing. Medical diagnosis of various diseases, object recognition and character recognition are some specific areas in which MATLAB has been really useful. Now I am also researching in the area of data science. I have found it to be surprisingly and pleasantly useful in this area although people are making use of Python and its libraries and R for this purpose.

Puntos a favor: The abstraction of best of the cutting edge techniques scaled down to function level makes it powerhouse of research in the field of science and engineering. Input of data in the form of matrices make it intuitive to use and visualization of data makes it an extension of your own mind. It doesn't take much time before it gets you working with the lifeless data transforming it useful insights.

Contras: The black box approach of using functions wherein you are aware what the input and output of function is but not its source code is a double edge sword. Whereas it makes it easy to use the function per se but it also makes it difficult to customize software. The source code of the commonly used functions should be available.

"Analysis, Calculations and Simulation (All in One)"

Comentarios: Superb, great, learning, knowledgeable, professional, expertise and outstanding

Puntos a favor: Matlab is not just a software but its an language for the next generation engineers. I started using Matlab after I came to Germany for my masters. In almost every subject at my university I have to use Matlab. In my subject computer-based measurement technology i firstly used it and also completed a Mathwork training of Cody course work. Its an training for beginner. I love that session as it explains each and every command with its proper justification. I also used Matlab for solving temperature resolution problems across a given cube or structure. It gives an analytical diagram of flow of heat throughout the structure. Thus a wide range of analysis can be done in Matlab. But the most appreciated feature is the Matlab simulink, it is just a pack of things which creates the simulation and provides relevant outlet. I am not practically used it but I had worked over it in my subject simulation of mechanical systems. Really Matlab is like a tip of an Ice berg. The more you go the deeper is the knowledge. I own a license version of Matlab by my university.

Contras: I didn't have any major critics over Matlab. But I will definitely gives a suggestion of CFD analysis of fluids and flows as if it was done in Ansys.If Matlab team is able to provide that feature of CFX simulation in future.

"Handy for data scientists - frustrating for developers"

Puntos a favor: For mathematicians and data scientists, MATLAB is easy to pick up and intuitive to use.

Contras: As a developer, I have a few issues with MATLAB. Its best practices would generally regarded as bad practices in other languages, meaning that experience often doesn't translate. When developing modular and extensible applications, MATLAB's runtime performance seems to degrade when compared to other languages, despite uitilising Java for a number of backend processes. Frequently, when working with legacy MATLAB code, I often find myself thinking that a given task could be easier achieved and made more maintainable with Python and its innumerable free packages, in contrast to MATLAB's toolboxes, which tend to require more money.