Neural Networks and Deep Learning: Crash Course AI #3

You can learn more about CuriosityStream at https://curiositystream.com/crashcourse.
Today, we're going to combine the artificial neuron we created last week into an artificial neural network. Artificial neural networks are better than other methods for more complicated tasks like image recognition, and the key to their success is their hidden layers. We'll talk about how the math of these networks work and how using many hidden layers allows us to do deep learning. Neural networks are really powerful at finding patterns in data which is why they've become one of the most dominant machine learning technologies used today.

Crash Course is on Patreon! You can support us directly by signing up at   / crashcourse  

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

Eric Prestemon, Sam Buck, Mark Brouwer, Timothy J Kwist, Brian Thomas Gossett, Haxiang N/A Liu, Jonathan Zbikowski, Siobhan Sabino, Zach Van Stanley, Bob Doye, Jennifer Killen, Nathan Catchings, Brandon Westmoreland, dorsey, Indika Siriwardena, Kenneth F Penttinen, Trevin Beattie, Erika & Alexa Saur, Justin Zingsheim, Jessica Wode, Tom Trval, Jason Saslow, Nathan Taylor, Khaled El Shalakany, SR Foxley, Sam Ferguson, Yasenia Cruz, Eric Koslow, Caleb Weeks, Tim Curwick, David Noe, Shawn Arnold, William McGraw, Andrei Krishkevich, Rachel Bright, Jirat, Ian Dundore
--

Want to find Crash Course elsewhere on the internet?
Facebook -   / youtubecrashcourse  
Twitter -   / thecrashcourse  
Tumblr -   / thecrashcourse  
Support Crash Course on Patreon:   / crashcourse  

CC Kids:    / crashcoursekids  

#CrashCourse #ArtificialIntelligence #MachineLearning