Fall 2020 - EENG 439/ ENAS 940 Neural Networks and Learning Systems

Course Description: Neural networks (NNs) have become all-pervasive giving us self-driving cars, Siri Voice assistants, Alexa and many more. While deep NNs deliver state-of-the-art accuracy on many artificial intelligence tasks, it comes at the cost of high computational complexity. Accordingly, designing efficient hardware architectures for deep neural networks is an important step towards enabling the wide deployment of NNs, particularly in low-power computing platforms, such as, mobiles, embedded Internet of Things (IoT) and drones. This course aims to provide a thorough overview on deep learning/neuromorphic computing techniques, while highlighting the key trends and advances toward efficient processing of deep learning and spike-based computing in hardware systems, considering algorithm-hardware co-design techniques.

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