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MATLAB vs R: What are the differences?
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Syntax: MATLAB uses a more intuitive syntax similar to traditional mathematical notations, making it easier for beginners to understand and write code. R, on the other hand, has a more complex syntax with extensive use of brackets and parentheses.
Flexibility: MATLAB is primarily designed for numerical computing and matrix operations, while R is a language specifically designed for statistical computing and graphics. This difference in focus gives R an edge when it comes to complex statistical analysis and visualization tasks.
Cost: MATLAB is a commercial software and requires a paid license for full functionality, which can be a significant cost barrier for individual users or organizations. R, being open-source, is free to use and has a vast community contributing to its development and support.
Graphics: R offers superior data visualization capabilities through its wide range of packages like ggplot2, lattice, and plotly, which provide more customization options and better quality of graphs compared to MATLAB's plotting functions.
Community Support: The R community is known for its active participation and collaboration, offering a wealth of resources, extensive documentation, and frequent updates to packages. MATLAB, while having a strong user base, may lack the same level of community engagement and support.
Interoperability: While both MATLAB and R can integrate with other programming languages, MATLAB is more commonly used in engineering and scientific applications due to its compatibility with tools like Simulink for simulation and modeling, whereas R excels in statistical analysis and research with seamless integration with databases and web applications.
In Summary, MATLAB and R differ in syntax, flexibility, cost, graphics, community support, and interoperability, catering to diverse needs in numerical computing and statistical analysis.
MACHINE LEARNING
Python is the default go-to for machine learning. It has a wide variety of useful packages such as pandas and numpy to aid with ML, as well as deep-learning frameworks. Furthermore, it is more production-friendly compared to other ML languages such as R.
Pytorch is a deep-learning framework that is both flexible and fast compared to Tensorflow + Keras. It is also well documented and has a large community to answer lingering questions.
Pros of MATLAB
- Simulink20
- Model based software development5
- Functions, statements, plots, directory navigation easy5
- S-Functions3
- REPL2
- Simple variabel control1
- Solve invertible matrix1
Pros of R Language
- Data analysis84
- Graphics and data visualization63
- Free54
- Great community45
- Flexible statistical analysis toolkit38
- Easy packages setup27
- Access to powerful, cutting-edge analytics27
- Interactive18
- R Studio IDE13
- Hacky9
- Shiny apps7
- Shiny interactive plots6
- Preferred Medium6
- Automated data reports5
- Cutting-edge machine learning straight from researchers4
- Machine Learning3
- Graphical visualization2
- Flexible Syntax1
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Cons of MATLAB
- Parameter-value pairs syntax to pass arguments clunky2
- Doesn't allow unpacking tuples/arguments lists with *2
- Does not support named function arguments2
Cons of R Language
- Very messy syntax6
- Tables must fit in RAM4
- Arrays indices start with 13
- Messy syntax for string concatenation2
- No push command for vectors/lists2
- Messy character encoding1
- Poor syntax for classes0
- Messy syntax for array/vector combination0
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What is MATLAB?
What is R Language?
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What companies use R Language?
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