About this Class

In this hands-on virtual lab, the participants will familiarize themselves with Deep Learning concepts and techniques, using MATLAB Online to train deep neural networks on GPUs in the cloud, create deep learning models from scratch for images and signal data, explore pretrained models and use transfer learning, import and export models from Python frameworks such as Keras and PyTorch, as well as automatically generate code for embedded targets. Deep Learning can achieve state-of-the-art accuracy when it comes to complex problems such as image classification or developing predictive models for signal processing applications. Deep Learning outperforms humans in some tasks like classifying objects in images. Cancer researchers are using deep learning to automatically detect cancer cells, for example.  This is an introductory class with a 3.5 hour duration, including a 20 minute break.