I run a neuroscience (brain science) research lab, in which we measure tiny electrical impulses generated by thousands of brain cells to understand how those cells process sensory information and coordinate with each other to produce brain activity that spans multiple orders of magnitude in time and in space. First and foremost, as a way to analyze large-scale, multivariate, multidimensional datasets. And this brings me back to the first paragraph of this blog: Should you learn MATLAB? If you are interested in learning or having a career in science, mathematics (abstract or applied), engineering, computational biology, physics, or data-oriented finance, then the answer is Yes, you should learn MATLAB. How can we make sense of the increasingly big data that these machines are giving us? I bet you can guess what I’m going to write next - put the data into MATLAB and do lots and lots of analyses, modeling, and visualization!Ĭomputer code that is optimized for data analysis, modeling, simulations, and visualizations is generally called “scientific programming,” and that is where MATLAB really excels. On the other hand, engineers, physicists, and biologists have developed incredible machines to measure the things inside the universe, everything from radars to thermometers to MRIs to tiny electrodes that measure the electrical impulse from individual brain cells. In fact, we understand so little of the universe that we don’t even understand how much we don’t understand. The universe is a really, really, really vast and complex place. But it retains its two core themes: An accessible language that non-programmers can easily learn and use and a strong focus on applied mathematics in education, research, and industry. Since those early days, MATLAB has grown to be much much more than a simple wrapper. MATLAB stands for “matrix laboratory.” The initial idea was to build up the wrappers for libraries that implement the numerical processing underlying mathematics, with a strong focus on applied linear algebra and matrix decompositions. In the early 1980’s, Moler joined forces with Stanford engineers Jack Little and Steve Bangert, and together they created the MATLAB program. This code allowed people to implement advanced mathematical formulas in FORTRAN libraries without having to master the FORTRAN language. A wrapper is easy-to-use code that calls hard-to-use code, like a translator from “simplified English” to ancient Tibetan. (Side note: people have struggled with programming for as long as there has been computers! You’re not the only one!).Įnter Cleve Moler, who developed a language that was essentially a “wrapper” for FORTRAN. Many people wanted to use computers for applied mathematics but struggled with writing computer code. But FORTRAN also isn’t a very user-friendly language. In the late 1970’s, the programming language FORTRAN was developed to help scientists and engineers implement mathematical formulas on computers (FORTRAN = formula translation). But more annoyingly, the available computer code was really difficult to learn. (If this paragraph seems like “ancient history,” then that’s great, because it means you are getting a jump-start on your career!) When computers started being used by universities and companies in the 1960’s and 1970’s, they were BIG (think about an entire room-sized computer that was basically just a fancy calculator). And then I’ll tell you how to get from the “baby-steps” of MATLAB programming to becoming a master MATLAB programmer. Instead, I want to tell you what MATLAB is really great at, where and how MATLAB is used, and what you will gain from mastering MATLAB. MATLAB is by far my favorite language, but I’m not going to try to sell MATLAB or convince you that you need to learn it. Every programmer has a favorite programming language, and they usually try to sell it like it’s the greatest language… “it’s the best language!”, “You gotta start learning this one!” and so on.
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