Compare GNU Octave and Scilab 
- Users report that GNU Octave excels in 3D/solid modeling tools with a score of 9.5, making it a preferred choice for users needing advanced visualization capabilities, while Scilab's score of 5.7 in this area indicates a significant gap in functionality.
- Reviewers mention that Scilab offers better collaboration features, scoring 8.5 compared to GNU Octave's 8.0, which is crucial for teams working on projects together.
- G2 users highlight that GNU Octave has superior data sampling capabilities with a score of 8.2, while Scilab shines in this area with a higher score of 8.9, indicating that Scilab may provide more robust tools for data analysis.
- Users on G2 report that both products have similar performance in regression analysis, each scoring 8.3, suggesting that users can expect comparable functionality in this critical statistical method.
- Reviewers say that GNU Octave's command clarity is rated at 9.0, which is significantly higher than Scilab's 8.3, indicating that users may find Octave's interface more intuitive and easier to navigate.
- Users report that Scilab's cost analysis tools are slightly better, with a score of 8.7 compared to GNU Octave's 8.5, suggesting that Scilab may offer more comprehensive features for financial modeling and analysis.
Octave is the best utility software which i have used for starting my machine learning.It is very easy to use and it is also very less demanding on cpu so,we can use it with an uninterrupted experience.It is very good for Algorithm development and it is...
Despite the language's well-optimized math functions, everything else just feels a bit too clunky and complicated for a high-level language. For instance, building functions and calling those functions
Really good software for higher and complex numeric analysis. This software is similar to the well known software MATLAB, but this is opensource, hence this is a free software. Highly recommended. Also is available on almost all platforms
Object oriented programming is quite complicated in Scilab
Octave is the best utility software which i have used for starting my machine learning.It is very easy to use and it is also very less demanding on cpu so,we can use it with an uninterrupted experience.It is very good for Algorithm development and it is...
Really good software for higher and complex numeric analysis. This software is similar to the well known software MATLAB, but this is opensource, hence this is a free software. Highly recommended. Also is available on almost all platforms
Despite the language's well-optimized math functions, everything else just feels a bit too clunky and complicated for a high-level language. For instance, building functions and calling those functions
Object oriented programming is quite complicated in Scilab
