The State of The Theory of Deep Neural Networks
A summary of the theory behind deep neural networks
Overview
For my final year research project in University, I wrote about the mathematical foundations of deep neural networks. In the document, I cover the mathematical basics behind neural networks, explore some more interesting architectures such as CNNs, Reinforcement Learning and Transformers, then wrap up with some experiments on the effects of varying the depth of these models.
This project involved
Research Skills:
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Combed through dozens of research papers over the course of the project
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Distilled key information in my own words to solidify my understanding
Python Machine Learning:
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Greatly improved my Python programming proficiency
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Coded many types of neural network using TensorFlow and from scratch
Presentation & Storytelling:
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Collated all relevant information in an organised and easy to follow narrative
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Presented information in a clear and consise manner so that readers unfamilar with the field can understand it.
If you're interested, you can read my full paper below :
This was my first ever academic research paper. I learned and honed so many new skills throughout this project, and I am thrilled with the result. The sense of satisfaction from finishing this was immense, and I would be very interested in potentially pursuing further research in this fascinating field!