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Which is better Octave or Python for machine learning?
Octave is good for developing Machine Learning algorithms for numeric problems. Python is a general programming language strong in algorithm building for both number and text mining. So whether you’re looking to learn simple regression or robotic vision, open source may have an ideal solution for you.
Should I use Matlab or Python for machine learning?
MATLAB is the easiest and most productive computing environment for engineers and scientists. It includes the MATLAB language, the only top programming language dedicated to mathematical and technical computing. In contrast, Python is a general-purpose programming language.
Is Octave same as Python?
1 Answer. Python is a programming language, just like Octave. So everything that can be done in Octave can be done using Python too.
Why octave is good for machine learning?
Octave is a high-level programming language that is typically used for scientific numerical calculations. Andrew Ng has used Octave and MATLAB in his course on machine learning. The reason is that these languages allow you to better understand the mathematics behind machine learning algorithms.
Does octave use Python?
At a high level, the features and capabilities of Octave’s Python interface allow a user to: Import and call any Python module or function from the Octave interpreter. Automatically convert basic Octave and Python types seamlessly between the two operating environments.
Can I use Octave in Python?
Oct2Py allows you to seamlessly call M-files and Octave functions from Python. It manages the Octave session for you, sharing data behind the scenes using MAT files. Usage is as simple as: >>> oc = oct2py.
Is octave online is good for machine learning?
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.
Which is better for machine learning Python or octave?
I don’t think Octave is better for machine learning than Python and, as pointed out by Oleg, Ng’s latest machine learning classes have switched to Python. At this point, Python has VASTLY more support for machine learning than Octave. Octave seems nearly moribund compared to either Python or R.
Which is better for machine learning Python or Julia?
Python: If you’re doing general machine learning or looking for a general purpose programming language, I’d recommend Python. Julia: If you’re doing machine learning or statistical computing and really, really care about speed, I’d recommend Julia. (In many bench marks it outperforms C.)
Which is better for ML, octave or MATLAB?
(Andrew Ng’s Coursera course is taught in Octave, which may give you the impression that it’s a popular language for ML, but my experience is similar to Jason’s: almost no one uses it for that.) R: If you’re doing statistical analysis and visualization, I’d recommend R.
Is the Andrew Ng Machine learning MOOC taught in octave?
A few months ago I had the opportunity to complete Andrew Ng ’s Machine Learning MOOC taught on Coursera. It serves as a very good introduction for anyone who wants to venture into the world of AI/ML. But the catch….this course is taught in Octave.