Neural Networks Part 5: ArgMax and SoftMax
When your Neural Network has more than one output, then it is very common to train with SoftMax and, once trained, swap SoftMax out for ArgMax. This video give you all the details on these two methods so that you'll know when and why to use ArgMax or SoftMax.
NOTE: This StatQuest assumes that you already understand:
The main ideas behind Neural Networks: https://youtu.be/CqOfi41LfDw
How Neural Networks work with multiple inputs and outputs: https://youtu.be/83LYR-1IcjA
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
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Chapters (6)
Awesome song and introduction
2:02
ArgMax
4:21
SoftMax
6:36
SoftMax properties
9:31
SoftMax general equation
10:20
SoftMax derivatives
Playlist
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Cutting Butter
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onion-dice
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R-squared, Clearly Explained!!!
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Wrapping up dumplings for pot stickers.
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The standard error, Clearly Explained!!!
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That Dude (in the movies)
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How to puree garlic
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Confidence Intervals, Clearly Explained!!!
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RPKM, FPKM and TPM, Clearly Explained!!!
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Principal Component Analysis (PCA) clearly explained (2015)
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StatQuest: RNA-seq - the problem with technical replicates
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That's Alright
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Christmas In Rio! (now on iTunes!)
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Drawing and Interpreting Heatmaps
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Rachel's Song (the ballad of Hazel Motes)
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Deal With It
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Say Your Goodbyes
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Another Day
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StatQuest: Linear Discriminant Analysis (LDA) clearly explained.
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Maybe It'll Go Away
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Nasty Weather
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Roses
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p-hacking and power calculations
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I Love You
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The Coldest Day of the Year
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Psycho Killer
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False Discovery Rates, FDR, clearly explained
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A New Song
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StatQuickie: Thresholds for Significance
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Logs (logarithms), Clearly Explained!!!
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Bar Charts Are Better than Pie Charts
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Mr Hattie
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StatQuickie: Which t test to use
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Fisher's Exact Test and the Hypergeometric Distribution
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Standard Deviation vs Standard Error, Clearly Explained!!!
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StatQuest: DESeq2, part 1, Library Normalization
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The Rainbow
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StatQuest: edgeR, part 1, Library Normalization
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The Main Ideas behind Probability Distributions
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StatQuest: One or Two Tailed P-Values
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Evil Genius
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Sampling from a Distribution, Clearly Explained!!!
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StatQuest: edgeR and DESeq2, part 2 - Independent Filtering
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The Main Ideas of Fitting a Line to Data (The Main Ideas of Least Squares and Linear Regression.)
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The Sum of Regrets
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Lowess and Loess, Clearly Explained!!!
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StatQuest: Hierarchical Clustering
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StatQuest: K-nearest neighbors, Clearly Explained
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Your Dark Side
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Boxplots are Awesome!!!
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What is a (mathematical) model?
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Linear Regression, Clearly Explained!!!
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Linear Regression in R, Step-by-Step
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Maximum Likelihood, clearly explained!!!
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Brothers
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Using Linear Models for t-tests and ANOVA, Clearly Explained!!!
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StatQuest: How to make a Mean Pizza Crust!!!
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StatQuest: A gentle introduction to RNA-seq
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I'm Alive
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StatQuest: t-SNE, Clearly Explained
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