MATLAB is a scripting language and environment for numerical computation, data analysis, and matrix operations. It’s used frequently in engineering and the natural sciences for its ability to crunch huge amounts of data and perform complex numerical operations quickly.
Key concepts
Courses
Basic programming and types
MATLAB’s most basic type is the matrix. All data (including variables and arrays) are stored as matrices (scalars are matrices. We declare row-by-row, where each element in a row is separated by a ,
and each row is separated by a ;
. To index the value at a specific index, we use parentheses, not square brackets: A(row, col)
.
MATLAB will display the contents of the declaration by default. To avoid this, we can add a semicolon to the end of the line.
Another basic type is the cell array. These are like regular matrices, except the contents of each cell can contain any type of data (including different ones). These are declared and accessed with curly brackets, but otherwise the same as regular matrices.
Addendums
Nowadays, Python is far more popular, in part because of libraries like NumPy and pandas. Inevitably, this also means MATLAB can be used for things like machine learning and Computer vision. But MATLAB has a broad amount of add-ons that cover broader fields in comparison.
The university’s MATLAB license comes with a shit ton of add-ons and toolboxes that cover just about everything — definitely something to explore. Highlights include deep learning, PDEs, signal processing, image processing, computer vision, lidar, medical imaging, reinforcement learning, communications, ROS, automated driving, and more. The point of using MATLAB is that you can basically do everything in a complicated project all in one platform (including testing and simulation).
MATLAB also lets us push things to hardware (without worrying what language is used) and different platforms easily.
re: deep learning we can analyse our big training things in the Deep Network Designer toolbox for matlab