Reece Teramoto, an application engineer at MathWorks, delivered a presentation expanding the audiences’ knowledge on deep learning using MATLAB and MathWorks. A person can use deep learning in a multitude of ways to advance research and create new opportunities in data science.
MATLAB deep learning is popularly used in various industries, such as oil and gas. It is utilized in various research, such as predicting gastrointestinal cancer and studying brain waves. Using deep learning in MATLAB and MathWorks can provide a multi-platform deployment for applications and systems. It can accelerate hardware and training, such as AI training on GPUs, without specialized programming.
Data preparation is significant in deep learning. Using MATLAB, users can reduce the time spent on preprocessing and labeling data. He discussed the differences between deep learning applications, such as mainstream vs engineering. Regardless of application, the underlying algorithms follow the same workflow.
MathWorks provides MATLAB deep learning courses, workshops and other resources people can utilize. Teramoto explained there is more to deep learning and data science than just algorithm development.
“The success in data science and machine-learning is more than just developing a good algorithm...it’s having a complete, cohesive workflow, from data access to algorithm deployment,” Teramoto said. For MATLAB and Online Training access, please visit the UH portal.