For the newbie of machine learning there is always confusion which scientific computing languages is best to start with?
- Matlab & Octave both are very powerful scientific computing languages
- Matlab provides variety of tools which helps users ease their task & It's a licenced version.Free trail is available.
- Octave is most powerful to solve linear & non-linear problems numerically,It's free,Open-Source scientific computing language available for use.
Summary : Each has its own high & low,Below is my view.
- Time VS Money
- Matlab which has variety of tools saves implementation time but costs the money,Most of the enterprises ready to get licences
- Octave(Free) saves money but implementation takes time compared to Matlab,In many scenarios we will be going with this to save the budget and try something new [Research]
- To look at career aspect ,Matlab is widely used in the current industry ,So better to start with this to grab best career opportunity.
- Since Matlab is widely used will get better help from community / documentation to pick quickly the learning curve.
- Over all if we are master at one of these language easy to switch other based on need,There will be syntax difference.
Matlab (matrix laboratory) developed by MathWorks. MATLAB allows matrix manipulations, plotting
of functions and data, implementation
of algorithms, creation of user interfaces, and interfacing with
programs written in other languages.
-->As of 2018, MATLAB has more than 3 million users worldwide
GNU Octave Primarily intended for numerical computations. Octave helps
in solving linear and nonlinear problems numerically, and for performing other
numerical experiments using a language that is mostly compatible with MATLAB.
It may also be used as a batch-oriented language. Since it is part of the GNU
Project, it is free software under the terms of the GNU General Public License.
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