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In the last video in this series, we discussed the biologically inspired structure of deep leaning neural networks and built up an abstracted model based on that. We then went through the basics of how this model is able to form representations from input data.
The focus of this video then will continue right where the last one left off, as we delve deeper into the structure and mathematics of neural nets to see how they form their pattern recognition capabilities!
00:00 Intro
0:34 How To Make A Neural Network
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Wyldn Pearson
Garry Ttocsra
Brian Schroeder
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Soundtrack ➤
♫ 00;00 "Clair de Lune" by RELAYER
♫ 00;34 "Sun" by HOME
♫ 03;00 "Flood" by HOME
♫ 06;16 "If I'm Wrong" by HOME
♫ 08;50 "Resonance" by HOME
♫ 12;13 "Accelerated" by Miami Nights 1984
♫ 13;03 "June" by Aire Atlantica
Sources ➤
[1]https://www.cs.toronto.edu/~hinton/ab...
[2] • How Deep Neural Networks Work (How Deep Neural Networks Work – Brandon Rohrer)
[3] • But what is a neural network? | Deep learn... (But What is A Neural Network? | Deep Learning, Chapter 1 – 3Blue1Brown)
[4] / understanding-activation-functions-in-neur...
[5]https://machinelearningmastery.com/re...
[6] • A Brief Introduction to Neural Networks (u... (Neural Networks [E01: Introduction] – Sebastian Lague)
Producer ➤ Ankur Bargotra
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