Is Octave worth learning in 2021?

Octave is good for machine learning in terms of helping you better grasp the mathematical intuition behind the algorithms. However, it’s not the best language for implementing ML or using it in production. Python has much better support for machine learning than Octave.

Do data scientists use Octave?

Octave can be used for solving various mathematical problems, building simulations, or working on data science projects. If you’re familiar with Matlab [2], or you’re looking for a quick way of prototyping your science-related ideas, you should definitely try Octave.

Why Octave is used?

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.

Is octave good for machine learning?

Octave is good for developing Machine Learning algorithms for numeric problems. If you don’t have time or need to learn an entire programming language, an online universe of open-source software can provide you with multiple solutions for your specific needs.

Is octave any good?

But Octave is free and good for the basic tasks that I do. If you are sure that you are going to do just basic stuff or you are unsure what you need right now, then go for Octave. You can pay for the MATLAB when you really feel the need.

Is octave important machine learning?

Octave (or its commercial version Matlab) is important in understanding machine learning because it allows you to easily prototype the entire machine learning framework without worrying too much on the programming specifics.

Is Octave good for machine learning?

How is Octave for machine learning?

Octave: If you are familiar with MatLab or you’re a NumPy programmer looking for something different, consider Octave. It is an environment for numerical computing just like Matlab and makes it easy to write programs to solve linear and non-linear problems, such as those that underlie most machine learning algorithms.

https://www.youtube.com/watch?v=39PyhM0LAow