Engineers who rely only on Python may find themselves encountering difficult or challenging tasks when it comes to embedded applications, building interactive dashboards, parallelizing applications, and deep learning. Contrarily, MATLAB® is a full-stack advanced analytics platform that empowers domain experts to rapidly prototype ideas, validate models, and push applications into production with ease; however, sometimes it is advantageous to integrate MATLAB and Python. One example is the need to combine the MATLAB library of advanced analytic capabilities with supplemental models available in the open source community. Another, using Python as a language that is well suited to pipe data between different IT systems or the web. 

 

There are several ways to integrate MATLAB and Python either as R&D tools or as scalable components of your production infrastructure. The latter gives business users and decision-makers immediate access to many of the built-in analytic capabilities in MATLAB from deep learning, optimization, signal and image processing, computer vision, data mining, time-series forecasting, embedded code generation, and more. 

 

Watch the many ways in which MATLAB and Python can interface and integrate with each other. 

 

Highlights include: