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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!

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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]
[2] (How Deep Neural Networks Work – Brandon Rohrer)
[3] (But What *is* A Neural Network? | Deep Learning, Chapter 1 – 3Blue1Brown)
[4]
[5]
[6] (Neural Networks [E01: Introduction] – Sebastian Lague)

Producer ➤ Ankur Bargotra

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10 COMMENTS

  1. Visit our parent company EarthOne for Sustainable Living Made Simple! https://earthone.io/

    – ALSO – Become a YouTube member for many exclusive perks from exclusive posts, bonus content, shoutouts and more! https://subscribe.futurology.earthone.io/member – AND – Join our Discord server for much better community discussions! https://subscribe.futurology.earthone.io/discord

  2. That feeling when no massive amount of rtx 3090 cards to train a neural network on. You should showcase Seth Bling's super mario world AI based on the NEAT algorithm and how this algorithm is changing the game.

    Neuro
    Evolution of
    Augmenting
    Topologies
    It's really tough stuff that requires vast knowledge of linear algebra and computers in general. That guy is really smart.

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