We have all used all the high end frameworks that works really well. How about writing a small strip down version of one. In this session, I’ll walk you through how to write a small Deep Learning Framework in Pure python and numpy which has auto grad and optimizers and easy to create models. Also, the framework will be extendible so that you can easily play around with.

Outline

• Computational graph and how it is usefull in moder day deep learning.
• Bare basics Computations needed for Deep Learning
• Implenting the forward pass
• Implementing the auto grad
• The complete tiny frame

Requirements

Basic Knowledge in using Python and numpy.
Basic knowledge in any of the modern day deep learning frameworks.

Speaker bio

Nithish Divakar is a Computer Vision Research Engineer at Cogknit Semantics. He Is a masters graduate from IISc bangalore and has been working in deep learning for past 4 years. He has prior published research work in GANs and Image captioning. See everythingproject.in for more.