But What Is Overfitting in Machine Learning?

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What is overfitting? That's a question I get quite often by people starting out in Machine Learning. In this video, I explain the concept of overfitting, and give some examples of it.

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Oscar is a leader, educator and programmer specialised in Artificial Intelligence and Machine Learning who strives to build a world where all leadership spawns from an intrinsic compassion for others.

He is heavily interest in mindfulness and meditation and is a daily Brazilian Jiu-Jitsu practitioner. Furthermore, he Loves lifting heavy things and reads a lot of books and believes in a world where compassion and mutual understanding and respect permeate all of our actions.

🎉 Leader of the Year (2017, All Swedish Students)
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🎉 37/100 @ Sweden's Top Future 100 Leaders 2017

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OscarAlsing

Wtf you explained this WAY BETTER than the instructor in the $12.99Udemy course I bought.

sephdisclosed

Thank you, my uni professor recommended watching this video for overfitting. The explanation is so easy to understand, thank you very much!!!

yaningasemsin

this is the best overfitting explanation so far for me as a layman

nurariffinmohdzin

You made it very easy to understand.
Thanks, keep the good work!

gzuzchuy

I think it was a good short description of the problem but possibly a little lightweight

ianjohnson

So clearly explanation!! Keep going!! I'm super happy to find your channel.

rodi

Fun & Fumbles: Overfitting in Machine Learning Models

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MachinelearningwithPats

Very clear explanation of overfitting, thanks!

PartyRockAdviser

Very useful! waiting for your next videos

sarahwaldorf

Did you know you can curve fit with little lines as to pickup on subtlety better. All you do is you approach the equation for the next line and decend away from the equation of the current line as you graph from one line to another. Here's some Mathematica code for what this descreate curving looks like.

Plot[Piecewise[{{((0.5 - x)/

0.5) (x/2) + (x/0.5) (0.25 + (x - 0.5) 1.1),

x <= 0.5}, {((0.25 - Mod[x, 0.25])/0.25) (0.25 + (x - 0.5) 1.1) +

Mod[x, 0.25]/0.25 (0.525 + (x - 0.75) 1.25),

x > 0.5 && x <= 0.75}, {0.525 + (x - 0.75) 1.25, x > 0.75}}], {x,

0, 1}]

quosswimblik

Oh! That makes sense! Thanks for the "dog explanation" :)

tymothylim

very clean explanation of the concept!

tropicthunder

That's a short a sweet explanation. Thanks!

Yht

This video is underfitting the concept of underfitting itself.

lukeponies

Overfitting is when you train AI on rules instead of heuristics. It’s a problem that stems from training AI on overly homogenous data set.

kierand

Thankyou for the explanation. Nicely explained.

sabihullah

does the green line in the given corresponds to the overfitting to the model?

mohammedanees

Isn't dog's example is actually underfiting?

emilr

how can we avoid overfitting in ML ??

hindbelkharchiche

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