EPISODE · Jul 24, 2018 · 12 MIN
Loss Functions Explained
from Siraj Raval
Which loss function should you use to train your machine learning model? The huber loss? Cross entropy loss? How about mean squared error? If all of those seem confusing, this video will help. I'm going to explain the origin of the loss function concept from information theory, then explain how several popular loss functions for both regression and classification work. Using a combination of mathematical notation, animations, and code, we'll see how and when to use certain loss functions for certain types of problems. Code for this video: https://github.com/llSourcell/loss_functions_explained Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology This video is apart of my Machine Learning Journey course: https://github.com/llSourcell/Machine_Learning_Journey More Learning Resources: http://www.informit.com/articles/article.aspx?p=2447200&seqNum=2 https://medium.com/data-science-group-iitr/loss-functions-and-optimization-algorithms-demystified-bb92daff331c http://ml-cheatsheet.readthedocs.io/en/latest/loss_functions.html https://blog.algorithmia.com/introduction-to-loss-functions/ http://yeephycho.github.io/2017/09/16/Loss-Functions-In-Deep-Learning/ https://stackoverflow.com/questions/42877989/what-is-a-loss-function-in-simple-words http://rohanvarma.me/Loss-Functions/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Sign up for the next course at The School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693
What this episode covers
Which loss function should you use to train your machine learning model? The huber loss? Cross entropy loss? How about mean squared error? If all of those seem confusing, this video will help. I'm going to explain the origin of the loss function concept from information theory, then explain how several popular loss functions for both regression and classification work. Using a combination of mathematical notation, animations, and code, we'll see how and when to use certain loss functions for certain types of problems. Code for this video: https://github.com/llSourcell/loss_functions_explained Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology This video is apart of my Machine Learning Journey course: https://github.com/llSourcell/Machine_Learning_Journey More Learning Resources: http://www.informit.com/articles/article.aspx?p=2447200&seqNum=2 https://medium.com/data-science-group-iitr/loss-functions-and-optimization-algorithms-demystified-bb92daff331c http://ml-cheatsheet.readthedocs.io/en/latest/loss_functions.html https://blog.algorithmia.com/introduction-to-loss-functions/ http://yeephycho.github.io/2017/09/16/Loss-Functions-In-Deep-Learning/ https://stackoverflow.com/questions/42877989/what-is-a-loss-function-in-simple-words http://rohanvarma.me/Loss-Functions/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Sign up for the next course at The School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693
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Loss Functions Explained
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