Artificial Intelligence techniques like deep learning are introducing automation to the products we build and the way we do business. These techniques can be used to solve complex problems related to images, signals, text and controls. Deep learning can achieve state-of-the-art accuracy in many human-like tasks, such as naming objects in a scene or recognizing optimal paths in an environment.
The main tasks involved in deep learning are to assemble large data sets, create a neural network, to train, visualize, and evaluate different models, using specialized hardware - often requiring unique programming knowledge. These tasks are frequently even more challenging because of the complex theory behind them.
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Nestor Daniel Fernandez
Senior Application Engineer
Nestor Fernandez is a MATLAB Application Engineer with a specialization in Language for Technical Computation (LTC), particularly for Artificial Intelligence (AI) and Data Science. He holds a Masters degree in Applied Science from the National University of Kaohsiung and a Physics undergraduate degree from the University of the Philippines Diliman.
Nestor has a strong track record of delivering innovative solutions to complex technical problems. He has worked with companies like Petron, STEngineering, Analog Devices Inc among others to help automate and accelerate their workflows. He regularly leads workshops and seminars for Universities in the Philippines and ASEAN region on how to use MATLAB and Simulink for research and education.
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