Likelihood to Recommend I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
Read full review MATLAB really does best for solving computational problems in math and engineering. Especially when you have to use a lot of functions in your solving process, or if you have a nonlinear equation that must be iteratively solved. [MATLAB] can also perform things like integration and derivation on your equations that you put into it.
Read full review Pros Simple and elegant code writing ability. Easier to understand the code that way. The ability to see the output after each step. The ability to use ton of library functions in Python. Easy-user friendly interface. Read full review It has a very user friendly library which helps users learn this software fairly quickly in a short span of time. The graphical user interface provided by the software is really good. The code that a person writes allows options for debugging. One can visualize the flow of control of their code inside MATLAB. Read full review Cons Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings. Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name. Read full review MatLab is pricier than most of its competitors and because of this reason, many organizations are moving towards cheaper alternatives - mostly Python. MatLab is inefficient when it comes to performing a large number of iterations. It gets laggy and often crashes. Python is better in this regard. There is a limited number of hardware options (mostly NI) that can be connected directly to the data acquisition toolbox. Read full review Usability Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
Read full review MATLAB is pretty easy to use. You can extend its capabilities using the programming interface. Very flexible capabilities when it comes to graphical presentation of your data (so many different kinds of options for your plotting needs). Anytime you are working with large data sets, or with matrices, MATLAB is likely to be very helpful.
Read full review Support Rating I haven't had a need to contact support. However, all required help is out there in public forums.
Read full review The built-in search engine is not as performing as I wish it would be. However, the YouTube channel has a vast library of informative video that can help understanding the software. Also, many other software have a nice bridge into MATLAB, which makes it very versatile. Overall, the support for MATLAB is good.
Read full review Alternatives Considered With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike
PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
Read full review How MATLAB compares to its competition or similar open access tools like R (programming language) or SciLab is that it's simply more powerful and capable. It embraces a wider spectrum of possibilities for far more fields than any other environment. R, for example, is intended primarily for the area of statistical computing. SciLab, on the other hand, is a similar open access tool that falls very short in its computing capabilities. It's much slower when running larger scripts and isn't documented or supported nearly as well as MATLAB.
Read full review Return on Investment Positive impact: flexible implementation on any OS, for many common software languages Positive impact: straightforward duplication for adaptation of workflows for other projects Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration Read full review MATLAB helps us quickly sort through large sets of data because we keep the same script each time we run an analyzation, making it very efficient to run this whole process. The software makes it super easy for us to create plots that we can then show to investors or clients to display our data. We are also looking to create an app for our product, and we will not be able to do that on MATLAB, therefore creating a limiting issue and a new learning curve for a programming language. Read full review ScreenShots