Convolutional Neural Networks Explained (2nd Offering)
Presenter: Ali Forooghi
Date: Friday, October 24th, 2025
Time: 12:00 pm
Location: Workshop Space, 4th Floor - 300 Ouellette Ave., School of Computer Science, Advanced Computing Hub
Convolutional Neural Networks (CNNs) have revolutionized the field of computer vision by enabling machines to see, recognize, and understand visual data with human-like accuracy. This workshop will demystify CNNs by exploring their internal structure, mathematical foundations, and the intuition behind how they learn visual patterns. Attendees will gain a clear understanding of convolutional layers, pooling, activation functions, feature maps, and how these components interact to perform complex visual recognition tasks. Practical demonstrations using Python and TensorFlow/PyTorch will illustrate how CNNs are trained and visualized.
- Introduction to Deep Learning and Neural Networks
- Core Components of CNNs
- CNN Architecture Design
- Training CNNs
- Visualization and Interpretation
- Basic understanding of Python programming
- Familiarity with fundamental ML concepts (No prior deep learning experience required)
Ali Forooghi, a Ph.D. student in computer science at the University of Windsor with an interest in Natural Language Processing. (Email: foroogh@uwindsor.ca)