Matlab is a programming language similar to other well-known languages such as Java, C#, etc., which comes with its own IDE (that is Integrated Development Environment) and set of libraries. Matlab is an abbreviation of the term “Matrix Laboratory” since it was initially referred to as the matrix programming language. It is a fourth-generation programming language. It was first discovered by Cleve Moler, who at the time was the Chairman of the Computer Science department at the University of New Mexico. His goal was to find an alternative way to perform linear algebra and numerical computation for his students without them having to use Fortran. Later in 1984, Cleve Molar along with Steve Bangart and Jack Little – who recognized Matlab’s commercial potential, found MathWorks. MathWorks released its first official version of Matlab in 1984.
- Performing numerical linear algebra
- Numerical computation of Matrices
- Data analysis and visualization
- Plotting graphs for larger data sets
- Developing algorithms
- Creating interfaces for the user that is the GUI- Graphical User Interface and other applications that is the API – Application Programming Interface.
Understanding the Matlab
In simple words, It is an advanced and more sophisticated version of a calculator that can be run on your computer or mobile device. One can use it to perform operations by making use of the command line interface as well as a text editor. It can also be used for writing programs and functions that perform continual tasks. The Matlab IDE contains a “help” icon, which consists of a detailed explanation of its workings. This feature is highly beneficial for people just getting started with Matlab.
How does Matlab make Working so Easy?
It makes your code fast. Your code is compiled using JIT- just-in-time compiler, library calls are optimized and tasks to perform math operations are distributed among the computer’s cores. With Matlab, one can run algorithms in parallel making the execution faster. As compared to Java, the development of algorithms in Matlab is much faster and more robust. It allows you to load data from different sources and visualize them. Matlab’s IDE provides access to interactive applications that enable you to perform computational operations interactively by providing you visuals of these operations. Allowing you to visualize how different algorithms interpret your data. One could also design their own customized applications as well as use applications designed by other Matlab users.
What can you do with Matlab?
Using Matlab you can implement and design different algorithms. You can load data from different sources such as files, databases or the web to analyze your data and visualize it using Matlab visualization application which gives you a wide range of graph plots to choose from. It also makes it easier to work with larger data sets. It as a math product contains a mathematical function library that allows you to perform linear algebra and computation of matrices. This also helps to facilitate data analysis. Creating data models, prototypes, and simulations of data can be achieved. You can also design interfaces for both users as well as other programming applications to make working with Matlab easier.
- It provides the fastest IDE for the mathematical computation of matrices and linear algebra.
- Contains the best mathematical package libraries to provide support for all fields of mathematics, ranging from simple summation to matrix inversion, etc.
- It provides multi-threading support and garbage collection to facilitate the parallel execution of algorithms.
- Its graphics system (Simulink) includes commands for two-dimensional and three-dimensional data visualization, image processing, graphics presentation, and animation providing high-quality visualization of plots and charts.
In order to get started with Matlab, one should have knowledge of basic object-oriented programming language and be aware of Matlab’s syntax. Have a good knowledge of the workings of Simulink. One should also possess a good understanding of advanced mathematics. Being familiar with its set of libraries and packages are required to carry out various mathematical operations. Knowing how to use the various built-in tools provided by the Matlab IDE to make one’s work faster.
Why should we use Matlab?
Matlab is one of the best technologies available in the market for mathematical operations performed on matrices and linear algebra. It also provides the best support for faster and better algorithm design and testing. It makes analyzing data with different algorithms and studying the changes in behavior easy. It also provides flexibility to design new interfaces as per ones need.
Matlab has its application across various functional fields such as finance, business, science, and engineering.
Why do we need Matlab?
Using MATLAB allows us several advantages over other languages and methods.
- By using toolboxes one could greatly enhance Matlab’s functionalities. For example, Statistics Toolbox facilitates specialized statistical manipulation of data, Excel link lets the data to be written in a format which is readable by Excel.
- MATLAB considers every single data element as a matrix. For example, an integer would be treated as a matrix of one row and one column. It provides built-in functions for matrix-based operations such as matrix addition, multiplication, inversion, etc.
- It considerably reduces the size of the code by using Vectorized operations.
- Simulink – Matlab’s graphics system provides optimized output for interaction. Making it easier to plot data and allowing one to customize its size and color.
Who is the right audience for learning Matlab technologies?
Engineers in the field of Data Science will find it useful for data analysis, data plotting and other detailed data related study. It is also for Scientists and research scholars dealing with advanced mathematical studies.
How this technology will help you in career growth?
Looking at the current boom in jobs for data analysis and data science, This could help you advance your career in these fields as it provides excellent features for analyzing data. It is also applicable in fields of deep learning, machine learning, signal processing and communication, computational finance, image and signal processing to name a few.