Neural Networks Pt. 2: Backpropagation Main Ideas

Backpropagation is the method we use to optimize parameters in a Neural Network. The ideas behind backpropagation are quite simple, but there are tons of details. This StatQuest focuses on explaining the main ideas in a way that is easy to understand. NOTE: This StatQuest assumes that you already know the main ideas behind... Neural Networks:    • The Essential Main Ideas of Neural Ne...   The Chain Rule:    • The Chain Rule   Gradient Descent:    • Gradient Descent, Step-by-Step   LAST NOTE: When I was researching this 'Quest, I found this page by Sebastian Raschka to be helpful: sebastianraschka.com/faq/docs/backprop-arbitrary.h… For a complete index of all the StatQuest videos, check out: statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - statquest.gumroad.com/l/wvtmc Paperback - www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - www.amazon.com/dp/B09ZG79HXC Patreon: www.patreon.com/statquest ...or... YouTube Membership: youtube.comhttps://www.seevid.ir/fa/result?ytch=UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: shop.spreadshirt.com/statques... ...buying one or two of my songs (or go large and get a whole album!) joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: twitter.com/joshuastarmer 0:00 Awesome song and introduction 3:55 Fitting the Neural Network to the data 6:04 The Sum of the Squared Residuals 7:23 Testing different values for a parameter 8:38 Using the Chain Rule to calculate a derivative 13:28 Using Gradient Descent 16:05 Summary #StatQuest #NeuralNetworks #Backpropagation

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