College Level Neural Nets [II] – Conv Nets: Math & Practice!

Learn about convolutional neural networks concepts, intuitions, mathematical derivations, and practical applications !

Created by: Ahmed Fathy, MSc
MSc, Senior Deep learning engineer @ Affectiva & Instructor

What Will I Learn?

• Deep understanding of convolutional neural networks [CNNs].
• Mathematical derivations for CNN-related tasks.
• Different types of convolutional neural network building blocks with their pros and cons.
• A lot of applications based on CNNs, with lots of tips and tricks.
• How to read and understand research papers in detail.

Requirements

• Have a prior good understanding of Neural networks, as this is the second course in the deep learning series.
• Have a proper understanding of basic linear algebra and calculus.

Target audience

• Computer science students wishing to learn about deep learning in good detail.
• Software developers with an interest in machine learning and deep learning.
• Deep learning practitioners hoping for more deep theoretical knowledge about the inner-workings of neural networks.