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Neural Networks: Crash Course Statistics #41

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Channel: CrashCourse
Categories: Computer Science   |   Statistics & Probability   |   Math   |   Science  
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Today we're going to talk big picture about what Neural Networks are and how they work. Neural Networks, which are computer models that act like neurons in the human brain, are really popular right now - they're being used in everything from self-driving cars and Snapchat filters to even creating original art! As data gets bigger and bigger neural networks will likely play an increasingly important role in helping us make sense of all that data.

Special thanks to Max Deutsch giving us permission to use his Neural Network-written Harry Potter chapter in this episode! Read more about his work here:
https://medium.com/deep-writing/harry-potter-written-by-artificial-intelligence-8a9431803da6

Neural Network to create anime characters:
https://arxiv.org/pdf/1708.05509.pdf

Neural Network to great Van Gogh-like art:
https://towardsdatascience.com/gangogh-creating-art-with-gans-8d087d8f74a1

Neural Network to create skate decks:
https://github.com/RJT1990/gandecks/

Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse

Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever:

Sam Buck, Mark Brouwer, Jennifer French Lee, Brandon Westmoreland, dorsey, Indika Siriwardena, James Hughes, Kenneth F Penttinen, Trevin Beattie, Satya Ridhima Parvathaneni, Erika & Alexa Saur, Glenn Elliott, Justin Zingsheim, Jessica Wode, Eric Prestemon, Kathrin Benoit, Tom Trval, Jason Saslow, Nathan Taylor, Brian Thomas Gossett, Khaled El Shalakany, SR Foxley, Sam Ferguson, Yasenia Cruz, Eric Koslow, Caleb Weeks, Tim Curwick, D.A. Noe, Shawn Arnold, Malcolm Callis, Advait Shinde, William McGraw, Andrei Krishkevich, Rachel Bright, Kathy & Tim Philip, Jirat, Ian Dundore
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