Welcome back to SIGAI! 😃 Tonight we'll go over some changes that have happened over the summer, how we'll handle things after moving forward, then dive into our classic first lecture/workshop series, An Intro to Neural Nets. This time, though, we'll go into significantly more depth, historically and mathematically, than we have in the past. See you there!
You've heard about them: Beating humans at all types of games, driving cars, and recommending your next Netflix series to watch, but what ARE neural networks? In this lecture, you'll actually learn step by step how neural networks function and learn. Then, you'll deploy one yourself!
Abstract: We present an application of back-propagation networks to hand-written digit recognition. Minimal preprocessing of the data was required, but architecture of the network was highly constrained and specifically designed for the task. The input of the network consists of normalized images of isolated digits. The method has 1% error rate and about a 9% reject rate on zipcode digits provided by the US Postal Service.