So far, this series has explained how very simple Neural Networks, with only 1 input and 1 output, function. This video shows how these exact same concepts generalize to multiple inputs and outputs and provides a context within we can discuss SoftMax and ArgMax for modifying the output data. NOTE: This StatQuest assumes you already know... The main ideas behind Neural Networks: https://www.youtube.com/watch?v=CqOfi41LfDw The ReLU Activation Function: https://www.youtube.com/watch?v=68BZ5f7P94E For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: null ...a cool StatQuest t-shirt or sweatshirt: null ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 2:07 Multiple inputs and outputs 3:57 The blue bent surface for Setosa 6:28 The orange bent surface for Setosa 6:52 The green crinkled surface for Setosa 8:42 Predicting Setosa 9:42 Versicolor 11:11 Virginica #StatQuest #NeuralNetworks