Deep learning, a chief driver of the AI revolution, can achieve state-of-the-art accuracy in many cognitive or perceptual tasks such as naming objects in a scene or recognizing optimal paths in an environment.
It involves assembling large data sets, creating a neural network, and training, visualizing, and evaluating different models, using specialized hardware - often requiring unique programming knowledge. These tasks are frequently even more challenging because of the complex theory behind them.
In this seminar, we’ll demonstrate new MATLAB features that simplify these tasks and eliminate the low-level programming. We’ll build and train neural networks that recognize handwriting, categorize foods, classify signals, and control machines.