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Convolution Network in vanilla Python


This workshop aims at providing the attendees an experience of implementing convolution neural from scratch without any big frameworks working in the backend supplementing the need for computation. This would give the attendees an overall understanding of what are Convolution Neural Networks and why do they work so exceedingly well in image processing!

This session would basically focus on python and it's ecosystem and how well it goes up with the current research paradigm shift that is happening due to the boom in Artificial intelligence. The session would help developers to amass the importance of mathematics and the ease that python provides in coding it, even from scratch. This would encourage the developers only to try more and more python programming for deep learning. For a nascent developer, this session packs in a high educational reward as he will be exposed to the mathematics behind the most successful algorithm of the past couple of decades.

This workshop aims to provide a look through the abstraction offered by big frameworks for developers to understand why mathematics behind data science is necessary yet, give them the insight into why abstraction is a key player in deep learning.

Q. What can developers expect from this workshop! Understand what are convolution neural networks Why they work so well on image data? All the different implementation of Convolution network and how they improve the vanilla network What are the best ways to implement convolution network on a given data

Q. What this workshop is not! Just another workshop telling you to use frameworks Mathematics will not be looked over. (It's important) This session would provide a much-needed exposure to python programming language and how its ecosystem helps deep learning so well.


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