Machine Learning Tutorial Python - 20: Bias vs Variance In Machine Learning

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Bias variance trade off is a popular term in statistics. In this video we will look into what bias and variance means in the field of machine learning. We will understand this concept by going through a simple example of house price prediction and also cover overfitting, underfitting.

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❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.
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Комментарии
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So thankful for the efforts. I am taking a AIML certification and key concepts seem to be missed. I am literally using your videos in parallel with the class to close gaps and improve my understanding. I teach SAP courses and Power BI, so I understand the time it takes to create quality training videos. The ability to take complex subjects and explain them in such a way my grandpa could understand it, is a skill. Hats off to you sir.

kentsuper
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This entire series is fabulous and super relevant!! Thank you for these videos, greatly appreciated!!

daniellemccorkle
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That is the best explanation of bias/variance tradeoff on Youtube. I wish you will make a series on advanced level machine and deep learning. Especially about the underlying math.

zehaia
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You deserve an award for making concepts clearer!

tesfayesusyimenu
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great presentation i ever saw . I can clearly see that how test error depends on selection of train datapoints . Thankyou sir

prathameshmore
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Wow. Such an amazing explanation. I watched 3 videos before yours and none were as explanatory as yours!!!

ontreprenor
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This is a very owsome course designed by you sir. Thanks for your efforts.

prayagrajchaudhary
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This is very genius example of underfitting and overfitting. Love it and thanks, haha.

tharlinhtet
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Thank you sir for teaching everything simple. It is easy to remember also. Great!!

vinayak
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Hats off to you to explain in such a simple way

artiverma
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superb video. Far superior to the Lectures by IIT profs on this subject. Great work and wishing yoy great success in the future

bakerkar
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Thank you so much for such a clear illustration and explanation

chuckyneoable
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Well explained! Thanks for the effort Sir!!

adityaaggarwal
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thank you so much for the constructive and clear explanation

danielasefa
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Very great explanation. Thanks so much for that

abdolrezamohseni
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Hats Off to you and your efforts, you are simplifying ML for this generation. Your way of teaching is irreplaceable!❤

Marshall_Mohammed
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Thanks for your Ameging Video, this video clear my concept about Bias and Variance...

redzone
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Hi,

Great content. The best in YT on bias and variance. I have a doubt - from 07:35 - 07:40 in the video, while we are looking at an ideal model, there are two curves which have been shown - meaning these are two different models. I thought we are looking into finding a single model which has a balanced fit. While we are varying the training dataset, the model also is changed. I feel it should the same curve for different training datasets.

Regards,
Krish

kmnm
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Best, detailed and intuitive example that is TRULY understandable. Never seen something some like this before. Thank you!!!

dataguy
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Sir cant we compare bias and variance on the one random dataset? is it always comparison between two data set test error and conclude the variance ? or two dataset train error and compare the bias ?

gargisingh