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Every Distance in Data Science (Almost 100K Subs!)




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Information Every Distance in Data Science (Almost 100K Subs!)


Title :  Every Distance in Data Science (Almost 100K Subs!)
Lasting :   21.25
Date of publication :  
Views :   12 rb


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Description Every Distance in Data Science (Almost 100K Subs!)



Comments Every Distance in Data Science (Almost 100K Subs!)



@trapItaliana
i cant believe you have a video for everything
Comment from : @trapItaliana


@includestdioh8492
Thank u professor!
Comment from : @includestdioh8492


@ben_jammin242
I'm liking your video WRT Euclidean distance, when you say it "doesn't make too much sense", it would have been nice to provide a little insight here as to why that is Haven't finished watching, but thanks for the content!brbrEdit: Fun and lively Engaging, with powerful explanations of things A-Grade teaching :-)!!! Also, nice pace and very calm :)
Comment from : @ben_jammin242


@pieter5466
16:26 I respect that you review and edit!
Comment from : @pieter5466


@ianambrose
Banger
Comment from : @ianambrose


@geoffreyanderson4719
Nice video
Comment from : @geoffreyanderson4719


@Parknparty
I have the same bar stools!
Comment from : @Parknparty


@paulhofmann3798
You forgot the distance of all distances the Kolmogorov complexity ie K(x|y) It’s incomputable but can be very well approximated for many use cases
Comment from : @paulhofmann3798


@Caesarr7
Hamming Distance is useful whenever there's sequence data, like in NLP applications (spell-checking) or bio-informatics (DNA), though it's usually better to use the more powerful Levenshtein distance
Comment from : @Caesarr7


@nuwaisir
What about the Jensen-Shannon distance (satisfies triangle inequality)?
Comment from : @nuwaisir


@sakib9419
Surprised the KL Divergence wasn't mentioned
Comment from : @sakib9419


@Break_down1
Excellent content!! Would love to hear how you’d explain Gaussian processes and Gaussian process regression
Comment from : @Break_down1


@peterhopkinson3040
100k is so well deserved, your content is so easy to understand and learn
Comment from : @peterhopkinson3040


@apterixbr
one more very intuitive video, thank you! maybe another one in the future about the steps (the intuition) to create your own distance model ps: let´s go to 500k! you are helping a lot of people to really understand the math using intuition instead of just read what is happening in some powerpoint we need more people like you teaching us :)
Comment from : @apterixbr


@rahulshah6119
12:08 I believe all Minkowski norms are convex so I don't think it is concave (I could be wrong though but visually it looks convex to me)
Comment from : @rahulshah6119


@kirudang
Congrats, you’re always my savior 😊 brThank you so much for all valuable lessons 🎉
Comment from : @kirudang


@bryceasay7749
That's the best explanation of chebyshev I have ever seen
Comment from : @bryceasay7749


@phamtam716
Hope you talk about hypebolic distance, is that same as haversine distance?
Comment from : @phamtam716


@advikdigitalarts
Are you Indian?
Comment from : @advikdigitalarts


@TheElementFive
Hamming distance is foundational to K-Modes Clustering, a neat and underrepresented algo Also, congrats on 100k!
Comment from : @TheElementFive


@stefanovNLP
one hundo, lets goooo
Comment from : @stefanovNLP


@CursedByManga
Random forest distance!
Comment from : @CursedByManga


@CodeEmporium
Almost there🎉
Comment from : @CodeEmporium


@init_yeah
Honestly you're a treasure in this age of misinformation
Comment from : @init_yeah


@man0utoftime
2:22 "to show how widely *this used is*" Sounds like German word order Lol
Comment from : @man0utoftime


@VivadiMusic
you deserve more 💙
Comment from : @VivadiMusic


@mikekertser5384
mahalanobis distance?brI'm wondering about a choice of right metrics to be invariant to a small distortions, measurement error or scaling
Comment from : @mikekertser5384


@videotrash
Congrats man! Appreciate all the work you've put into your videos and they've helped me out quite often
Comment from : @videotrash


@ChocolateMilkCultLeader
I've been sharing your stuff for a while Hopefully you blow up
Comment from : @ChocolateMilkCultLeader


@Set_Get
thank you for bringing up this topicbri hope you will have time to add/extemnd numerical examples for the less-used distancesbrthe fact that you break topics into 10 to 20 mins videos makes them more enjoyable
Comment from : @Set_Get


@_alt
Luv u!
Comment from : @_alt


@jont3901
first!
Comment from : @jont3901



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