Bias and Variance for Machine Learning | Deep Learning

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Do you know what bias and variance are? These are some of the key concepts of data science. Although crucial to know, it is not always easy for even data scientists to understand these concepts clearly. So in this video, we will go through the explanations of both bias and variance, basing their definition on logical ground.

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We will learn the implication of high bias and high variance and also how to address the issues created by high bias and high variance, namely underfitting and overfitting. We will talk about the bias-variance trade-off and why it is not as big of an issue as it used to be anymore.

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Bias = Assumptions ---> Underfitting
Variance = Sensitivity ---> Overfitting

You made it crystal clear, thank you.

AlexKashie

Explained a boring 30+ minute lecture to an easy, consumable less than 10 minute video. Well done!

roaklarson

Excellent description of a bias and variance!
Impatiently waiting for a new video!

unknownhero

Extraordinary explanation, thank you!

gaspad_

one of the best video out there comparing bias and variance. Thanks Assembly AI

anirbansarkar

the best video about the subject on the internet.

matinmahmoodi

Thank you so much for such an amazing explanation!

KhoulaAbdullah-zmlx

What is the difference between training the model more and introduce more data?

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When someone this cute teaches you can't help but give your 100% attention 😂

ashishpatil

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