Early Stopping. The Most Popular Regularization Technique In Machine Learning.

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Train a model for too long, and it will stop generalizing appropriately. Don't train it long enough, and it won't learn.

That's a critical tradeoff when building a machine learning model, and finding the perfect number of iterations is essential to achieving the results we expect.

Early stopping is one of the most popular regularization techniques to train machine learning models. It's both easy to implement and very effective.

📚 My 3 favorite Machine Learning books:

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Excellent high-level explanation of this topic. 10/10. Thank you for your hard work!

paulallen
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Wow, your teaching skills are excellent

aniketkumar
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You've got yourself a subscriber brother, great edit, clarity.

emresdance
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I just discovered one of the best channels

amedx
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implemented early stopping auto-saving best model for os-cnn, great explanation! I love your content

karlbooklover
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That was awesome! My teacher, my mentor, you are just the person I had the opportunity to learn from the most in my whole carrier. Thank you for sharing stuff like this and also for the time we spent working together in the past. I noticed you are now doing what you love the more... just keep teaching

alienm.nunezrivero
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One of the most interesting video to learn from. Thanks!

srishtigupta
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Supreme edit ! can't wait to see your channel grow ...

erfanelmtalab
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Awesome Explanation and The Thumbnail is lit 🔥

PritishMishra
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Sir your Explanation is excellent please make Videos on Regularization for Deep learning Parameter norm Penalties, Norm Penalties as Constrained Optimization

whilstblower
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This is exactly what I’m building! I’m creating variable training sets to see which training set size has best performance.

graysadler
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Great stuff! Looking forward to hearing more insights!

ЕгорАбросимов-ло
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Just what I was looking for ! how about doing a full machine learning course and simplify concepts with the same approach you did in this video ?

karimmerchaoui
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Really like the way you explained it, thanks a lot

alwaleedalattas
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I want to say one thing, As many times I see your videos, i get inspired to work on the suggestion and improve my model. ❤The best explanation ever. Watching over several times

nedafiroz
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Great explanation as always, Santiago 💯💯🔥

roshanaryal
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0:50 isn't this model over fitting to data?

aayushpatil
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OMG today itself I came across this confusion (I've just started ML, today started with linear regression, so it's not always linear ahh satisfaction :))

varunahlawat
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You sounds like a hero of all Machine Learning realm. Thank you very much for the video sir.

limotto
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Amazingly creative explanation, new sub ❤

Naeem