# Welcome to DATA621 - Neural Networks and Deep Learning#

(last update 10/7/2024)

This is the landing page for the course on Neural Networks and Deep Learning held at William & Mary during Fall 2024

Important

The lectures will take place at the Integrated Science Center, room 2291

**Synopsis**: Neural networks and deep learning have revolutionized the field of artificial intelligence, enabling breakthroughs in image recognition, natural language processing, and more. This course will explore the foundational concepts and practical applications of neural networks, covering how to build them from scratch as well as utilizing popular deep learning libraries. Students will delve into various architectures, including Multilayer Perceptrons (MLP), Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Graph Neural Networks (GNN), and more recent advancements. By the end of the course, participants will have hands-on experience and a deep understanding of both the theory and practice of neural networks and deep learning.

This course is based on the following references: [BGC17, KK22, RLM22]

**Credits**: Material on git, VS-Code, and HPC prepared by K. Suresh