With the resurgence of Neural Networks in the 2010s, Deep Learning has become essential for Machine Learning practitioners and even many software engineers. In this talk, I will start with Deep Learning basics and move quickly to the details of important advanced architectures, as well as how these basics are used in implementing Deep Neural Networks from scratch along the way. I will demonstrate on how Neural Networks work in a principled approach.

This talk will cover:
1. Neural Networks basics and Forward propagation
2. The importance of Back propagation
3. Optimisation Algorithms
4. Perform train/test splits and examine production case studies

This seminar is available on my Youtube: https://www.youtube.com/watch?v=IuNEfmuoEuM&t=369s&ab_channel=Codementor