Likelihood to Recommend 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 They have created Pytorch Lightening on top of Pytorch to make the life of Data Scientists easy so that they can use complex models they need with just a few lines of code, so it's becoming popular. As compared to
TensorFlow (
Keras ), where we can create custom neural networks by just adding layers, it's slightly complicated in Pytorch.
Read full review Pros 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 Provides Benchmark datasets to test your custom algorithm Provides with a lot of pre-coded neural net components to use for your flow Gives a framework to write really abstract code. Read full review Cons 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 Distributed data parallel still seems to be complicated Support for easy deployment to servers Torchvision to have support for latest models with pertained weights Read full review Usability 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 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 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 As I described in previous statements, Pytorch is much better suited than
TensorFlow from a software development look. This Pythonic idea was then taken and repeated by all the other frameworks. You can get to better performance models by better understanding the deep learning model code, so I think the choice of Pytorch is easy and simple.
Read full review Return on Investment 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 I'd estimate I can build a model 50% faster on pytorch vs other frameworks Read full review ScreenShots