Supervised & Unsupervised Machine Learning

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[Tier 1, Lecture 4b] This video describes the two main categories of machine learning: supervised and unsupervised learning. Supervised learning involves labeled training data, where the ground truth is included in the training data, while unsupervised learning does not include these labels.

This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company

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0:00 Overview
1:45 Detailed Categorization of Machine Learning
2:19 Supervised vs Unsupervised Learning
8:07 Reinforcement Learning
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You identified a simple cluster of knowledge, you did not go too deep, instead gave a clear presentation and explanation without any distraction. Well done, thank you.

zoltantoth
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A very useful series to share with those that ask me how all of this works. Thanks! Enjoyed the "New Advances" video, as well. Cheers

algorithminc.
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Wow ... super clear and well presented. Thank you! Going to look for more of these videos.

levon
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Oh boy, we're in for a treat on this topic! Thank you !!

et
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A premium video to watch on the last day of 2023!

ec
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This was brilliant
.
Cleared up so much of my hitherto unknown confusion....esp the fact that not ALL ml is neural networks. Really didny know that...yes, heard about the others like svd, decision trees, etc. But didnt put them in the ml sphere.

tyronefrielinghaus
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Fantastic. I'm a mathematician wanting to get into ML and this has been a nice overview.

Can I ask how you create these presentations? I've never seen someone interact with a visualization in this way? Does the technique have a name I can Google? Thanks.

bencrossley
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Thank you Professor Brunton for always giving highly content videos with such clear explanations. Even for professionals like me who have worked with data science for almost a decade, it is very elucidating. Do you plan to make a video explaining how deterministic and stochastic control techniques may be applied to physical systems, and which one is more suited for each case?

thiagocesarlousadamarsola
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Thanks for your clear presentation. Would you please give more details about “labeled”? Thanks

beigou
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is this part of a playlist? I looked for one for just machine learning, but didn't find one, and I really would like to see all the related videos.

TheLostBijou
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Am grateful for this lecture. Its been really simplified to my understanding

dukeubong
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Professor, I am thankful for these lectures you take time to post. I am taking a class in AI for industry and we used PCA, FFT, SVM, SOM, Logistic Reg., and regression. I will appreciate if you could make a video on Self organizing maps and Support vector machines, especially how to implement in MATLAB and python. Thanks so much

michaeltamajong
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Always a pleasure your videos- thx for sharing your knowledge

adntro-genetics
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we appreciate your effort to do that wonderful lecture, you are my hero...
I am from Kurdistan-Slemany city.

asosalih
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thank you for this, it's amazing intro about this field, keep on and deep dive in this field, again and again thank you ^ ^

OmarAhmed-injj
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My bachelor project is:
Airfoil Aerodynamics Coefficient Estimation using Neural Network-based mode.

AliMousavinejad-Aerospace
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Than you so much professor Steve brunton for wonderful explanation 😄😄

durgeshzaware
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gradients and automatic differenciation

tomoki-vo