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Orthogonality and Orthonormality 

Professor Dave Explains
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29 сен 2024

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Комментарии : 76   
@pkasb90
@pkasb90 4 года назад
I must say your lecture supercedes those in higher institutions.
@STKeTcH
@STKeTcH 3 года назад
same
@miguelnuno928
@miguelnuno928 3 года назад
Correct
@BoZhaoengineering
@BoZhaoengineering 2 года назад
agreed.
@overl0ad816
@overl0ad816 Год назад
🤓
@julenekenyon3278
@julenekenyon3278 Год назад
I agree 💯. At this point you deserve my tuition!
@Robert-gr1cl
@Robert-gr1cl 5 месяцев назад
such good explanations, thanks
@kryptoid2568
@kryptoid2568 3 года назад
sir, the inner product notation reminds me of bra-ket notation
@isxp
@isxp 3 года назад
Good god, I wish I found this 8 weeks ago. The drop date for classes is the 30th. I ended up with 6% on my first midterm in Mathematical Physics. This class will haunt till the day I die. I'll probably know this material better than any of the classes I've taken, as I'll likely obsess over it for months.
@kartikkalia01
@kartikkalia01 3 года назад
I'm at same situation as yours, please suggest similar videos/playlist.
@mohammedbastaki2101
@mohammedbastaki2101 6 месяцев назад
same here pal
@ayazohdy6221
@ayazohdy6221 5 лет назад
Professor Dave explains 😂💕
@tadabae
@tadabae 3 года назад
my final exam is in 15 minutes and i stumbled across this channel. he explains this so clearly!! i wish i found this channel earlier omg
@beams9497
@beams9497 2 года назад
Haha saaaame
@macdonaldnnadi
@macdonaldnnadi Год назад
15 minutes is crazy dawg
@Bruhhhhhhhhhhhhhhhhhhhhhh
@Bruhhhhhhhhhhhhhhhhhhhhhh 2 года назад
3:05 "four SQUARED plus two SQUARED plus negative one squared" lol im dying and good vid overall
@banderallogmany1912
@banderallogmany1912 3 года назад
3:52 I didn't get how the length becomes 1!
@lingwaili1203
@lingwaili1203 4 года назад
Thank you so much! Professor Dave explains clearly so I can finally understand orthogonal
@ddiverr
@ddiverr 4 года назад
clean, informative, and concise video, thanks guy
@kidatheart4975
@kidatheart4975 3 года назад
I'm confused on the orthonormal part. There are 2 conditions for orthonormal vectors: (1) orthogonal; and (2) the length is 1. But the example on 2:56, the length is not 1 that negate the conditions of being an orthonormal. Can you please elaborate that part? Thanks
@criclal1787
@criclal1787 3 года назад
Those vectors displayed at 2:56 are not orthonormal, we have converted them both to unit vectors and made them orthonormal thus.
@wealthy_concept1313
@wealthy_concept1313 2 года назад
@@criclal1787 but if that's the case it means any vector can be converted to orthonormal at will ?
@MuffinsAPlenty
@MuffinsAPlenty Год назад
@@wealthy_concept1313 Any set of vectors can be "normalized" (meaning to make the lengths of all of the vectors 1). This does not, at all, change the angles between any of the vectors. The Gram-Schmidt Process (the next video in the playlist) shows us that any _linearly independent_ set of vectors can be made orthogonal without changing the span of the set. Taken together, given any basis, we can always find an orthonormal basis by first using the Gram-Schmidt process to make the basis orthogonal without changing its span, and then we can "normalize" the orthogonal set to make it orthonormal.
@missghani8646
@missghani8646 4 года назад
can't thank you enough for this clear explaination
@rayandharia1718
@rayandharia1718 Год назад
CHEMISTRY JESUS CUT HIS HAIR
@mona5112
@mona5112 3 года назад
Hello Professor and Thanks for your great explanations. I was wondering why do not we have something called orthonormal matrices ?? and think orthogonal matrices are more like orthonormal ones!! :))
@deathworld5253
@deathworld5253 5 лет назад
Isn't orthagonality defined by having the dot product equal to null element in Euclidian space?
@yogsothoth2194
@yogsothoth2194 5 лет назад
I think null just means nothing; or in mathematical terms 0 . So yeah you're probably right
@asifnahyankabir7747
@asifnahyankabir7747 2 года назад
Amazing Professor! One day if God wills I'll come to meet you!
@user-rx9sj8mk8s
@user-rx9sj8mk8s 4 дня назад
This series is the easiest way to understand linear algebra. College professors get paid to teach this but they can't explain jack sh*t. Seriously this holds up today too.
@jainpravachan650
@jainpravachan650 3 года назад
Thanks sir.... wonderful lecture
@ManojKumar-cj7oj
@ManojKumar-cj7oj 3 года назад
Inverse of orthogonal matrix = tranpose of matrix
@건건-r7m
@건건-r7m 3 года назад
thanks for awesome explanations!!!
@raihansk5971
@raihansk5971 5 лет назад
Amazing!!.........Explaination is awesome.....
@rodab3546
@rodab3546 4 года назад
you explain so good
@bluefenix1457
@bluefenix1457 4 месяца назад
This explained it so well for me, you spoke clearly and didn't do messy sentences, and even paused after every sentence to process it 👏👏👏👏👏👏
@salmakhaled2397
@salmakhaled2397 14 дней назад
What is the w function at the end of the video?
@dgormley
@dgormley 3 года назад
Please teach at my university.
@apythonprogrammer7877
@apythonprogrammer7877 4 месяца назад
This really helped me understand LLM model quantization just a tiny bit better
@marcosramirez2278
@marcosramirez2278 2 года назад
I found this channel because of flat earth videos, never did I guess this man would save my math grade
@jds189
@jds189 4 года назад
what happened to the visuals clarifications? its been primarily plug and chug for most of linear algebra..
@janakamohotti
@janakamohotti 2 года назад
Brilliant explanation!!! ❤️
@jisaburo198
@jisaburo198 4 года назад
EXCELLENT videos! Thank you so much
@jaliyahkane5127
@jaliyahkane5127 3 года назад
professor dave is an AI
@adefisanadedotun797
@adefisanadedotun797 4 месяца назад
Very understood Thank you
@rushdisami5146
@rushdisami5146 2 года назад
Finally I understood Orthogonality.🤖
@JoseLopez-op7sq
@JoseLopez-op7sq 4 месяца назад
A lot of good information in one short video; good overview.
@garyallen538
@garyallen538 5 лет назад
Yeah but....what does this have to do with birds? (Sorry, couldnt resist!)
@mehuladhrit7883
@mehuladhrit7883 3 года назад
Very nicely taught...
@lamdawave
@lamdawave 2 года назад
Good video. One question: If a square matrix has orthogonal column vectors. its inverse is not equal to its transpose. what should we call this type of matrices?
@LivLiv-h4z
@LivLiv-h4z 9 месяцев назад
TE DUA
@mcalkis5771
@mcalkis5771 2 года назад
Could someone elaborate on the weight functions? Is it just a correction factor so that a function can be orthogonal with respect to another?
@glennveniceaboy8876
@glennveniceaboy8876 3 года назад
your convention for magnitude of a vector is a bit confusing because the single bar on both sides is usually for absolute value, maybe you should've used double bars for it anyways, i learned a lot, thanks!
@carultch
@carultch Год назад
Absolute value and magnitude of a vector have so much in common, they might as well use the same notation. I thought the double bars on both sides was completely unnecessary, when I was first introduced to the notation, after having become accustomed to just using the single pair of bars.
@manishbhatia2724
@manishbhatia2724 4 года назад
Beautiful Explanation
@tknam3278
@tknam3278 3 года назад
This is perfect!
@desrepeerc206
@desrepeerc206 2 года назад
3:23 Nice frankenbiting skills xD
@srinityapadma5125
@srinityapadma5125 3 года назад
Thank you so much Sir.../\
@Dixxi91
@Dixxi91 2 года назад
Very good explanation, thank you
@blakeelzinga1168
@blakeelzinga1168 3 года назад
Thank you for this video
@Gafa996Gaddisa
@Gafa996Gaddisa 5 лет назад
Is Ortho Greek word which means , straight up?
@georgesimos4914
@georgesimos4914 5 лет назад
"ορθό-ς" is used for other cases too; the one you say is one definition, but the one required for the concept of the video is "vertical"(an example is the mathematical expression "ορθή γωνία"="right angle")
@carultch
@carultch Год назад
@@georgesimos4914 Even though I know that 3 out of 4 of the letters have completely different pronunciations, I instinctively read "ορθή" as "open". Even though I know it would sound more like "orthi".
@AqibHussain-u1y
@AqibHussain-u1y 5 месяцев назад
Amazing explanation
@aniketgupta5750
@aniketgupta5750 3 года назад
Elaborate to some extent, I mean your beginning and laying down the foundation of the topic is good but should stretch it till good level. Atleast that's what I feel missing in your videos, do please consider this if you see this comment. By the way I love your videos from quantum numbers to biomolecules all are awesome.
@prakashraj4519
@prakashraj4519 3 года назад
video on caley hamilton
@colingillespie7635
@colingillespie7635 3 года назад
The intro alone earns my like
@suvarnamanojsingh
@suvarnamanojsingh 3 года назад
thanks that was helpful
@umehmoses8118
@umehmoses8118 Год назад
I love the professor 😁
@kaanylmaz1008
@kaanylmaz1008 2 года назад
eyw reis
@anandailyasa2530
@anandailyasa2530 3 года назад
❤️❤️❤️❤️❤️
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