Machine Learning and Deep Learning Series: Deep Learning and Neural Networks

Deep Learning and Neural Networks, the sixth lab of the Machine Learning and Deep Learning Series introduces participants to the fundamentals of deep learning and neural networks, focusing on their architecture and functionality. Attendees will explore how neural networks work, from input layers to output layers, and the role of activation functions. The session will also cover backpropagation, optimization techniques like SGD and Adam. Participants will gain hands-on experience by building a simple feedforward neural network for classification tasks. This session ensures participants understand the basics of deep learning and how it powers many AI applications today. 

During the Machine Learning and Deep Learning Open Lab Series, Namig Abbasov offers seven open labs to introduce participants to core concepts and techniques in Machine Learning (ML) and Deep Learning. These open labs will prioritize an intuitive understanding of machine learning algorithms and deep learning approaches. These are intended to complement machine learning and deep learning courses taught at ASU by focusing on intuitive explanations of difficult concepts and examples with analogical illustrations. 

Presented by Namig Abbasov with the ASU Library's Unit for Data Science and Analytics team.