Gentle Intro to Principal Component Analysis (PCA) --- Like, Subscribe, and Hit that Bell to get all the latest videos from ritvikmath ~ --- Check out my Medium: / ritvikmathematics
Пікірлер: 70
@jorostuff3 жыл бұрын
Finally, someone who introduces the problem first, the need, and then shows the solution. Most videos give you the solution and don't give you the problem at all, so you're left wondering why the thing exists in the first place. Great video!
@AJ-ks8iq3 жыл бұрын
The best comment I have read in forever.
@azamatbagatov49332 жыл бұрын
Better than Josh Starmer
@sanketannadate44072 ай бұрын
Really Great comment, coulnt agree more
@r0cketRacoon16 күн бұрын
@@azamatbagatov4933 ? Josh Starmer also does that
@isman323 жыл бұрын
This "high level" explanation was just what I needed to get rid out of doubts about how to implement PCA. Thanks so much for your effort. You got 1 new follower.
@ritvikmath3 жыл бұрын
Glad it helped!
@Ali_Alhawaj4 жыл бұрын
Finally, a clear video on PCA for a guy coming from biomedicine. Thank you!
@AJ-ks8iq3 жыл бұрын
I don't know if you realize how good you are!
@waynethompson83149 ай бұрын
I started teaching business analytics and find your teaching method as very consumable. Assuming length and weight of kitties is correlated I assume you could have just one PC.
@robertc63433 жыл бұрын
You have a rear gift of explaining things in a very clear way my friend. I’m curious to see the next video!
@ritvikmath3 жыл бұрын
Thank you very much!
@niamhtromans90863 жыл бұрын
Finishing a degree during COVID-19 and this man has explained better in 6 minutes what a lecturer I'm paying £9,000 spent 3 different 1 hour teams meetings trying and failing to explain
@sammyj293 жыл бұрын
One of the best channels which go in depth while still keeping it clear. Thank you for creating such content!
@AJ-ks8iq3 жыл бұрын
and not bore you with the math, if you don't need it.
@Information-Overlord2 ай бұрын
All the great reviews below are understatements ;-)
@zakzeaxer48683 жыл бұрын
looked a bunch of videos, but only this explained me well the interest of PCA !
@frenchmike6 ай бұрын
thanks for explaining it in plain english before going into some crazy math. I appreciate this
@sulaiman.micheal Жыл бұрын
You just saved me a lot of time and stress with this simple straightforward film. Thanks a lot. Please make another one like this on the fisher-face and LDA algorithm. 😇😇😇
@ritvikmath Жыл бұрын
Glad it helped!
@noahrubin3753 жыл бұрын
This was outstanding. Exactly what I needed.
@priyankagupta1192 жыл бұрын
When we study, our aim is to get clarity where we will use this concept, you explained it very well. Thank you so much.
@armonnaddaf53262 жыл бұрын
Hey Ritvik, I might be your biggest fan! Whether I'm cramming for an exam, trying to understand a paper, or just killing time on a curious Saturday, I always look for your videos first! That said, it would be very helpful if you could include a link to part 2 in your description or at the end of the video. Thank you for all you do :)
@viviann35404 жыл бұрын
Really like your explanation of PCA! I am a food microbiology Ph.D. student. Thank you for this great video! Hope more people can see this!Cheers!
@ritvikmath4 жыл бұрын
Glad it was helpful!
@francescodipietro43406 ай бұрын
Thanks man, i really need this kind of video to understand the topic
@fionadu-chan95316 ай бұрын
You are a genius!
@guilhermehx7159 Жыл бұрын
Very insightful
@ElectricTeaCup3 жыл бұрын
"We are cat researchers" *Instantly likes*
@ritvikmath3 жыл бұрын
:D
@user-xj4gg9jm3q2 жыл бұрын
fantastic video, the examples and using real numbers really clarifies things tysm !!
@salamkanada3 жыл бұрын
Great video! Clear and well explained. Really appreciate it. Thank you
@ritvikmath3 жыл бұрын
Glad it was helpful!
@hameddadgour Жыл бұрын
Great video! Thank you for sharing.
@sethquigley36772 жыл бұрын
Awesome work man! Thank you and God bless
@souravdey12273 жыл бұрын
Absolutely genius. I was looking for an intuitive understanding and here you se brother. Can you request you to do a few videos on locality preserving projection?
@user-tb5kz3mx9g7 ай бұрын
Very well explained. Thanks
@ritvikmath7 ай бұрын
Glad it was helpful!
@wasimasadia4887 Жыл бұрын
Nicely explained. Thank you.
@sArAsara-rr2qm Жыл бұрын
this video helpt me a lot thank u
@_Sam_-zh7sw9 күн бұрын
Bro. your videos are amazing and we really appreciate your work. But we are dependent on your channel so can you structure your content into bins of playlists? Or may be just make one playlist but arrange all videos in proper sequence.
@garcon2008 Жыл бұрын
This was excellent.
@mehdicharife23352 жыл бұрын
Thank you.
@manulwild69674 жыл бұрын
Great explanation, thank you!
@firstkaransingh2 жыл бұрын
Can you do a video comparing V.I.F and PCA and LASSO/RIDGE regularization. They seem to deal with very similar objective of multicollinearity. Excellent explanation as always.
@Paprika5263 жыл бұрын
This probably hurts me more than it should, but he means purr volume instead of purr frequency. Purr frequency is either the amount of times a cat purrs, or the tonal frequency on which the cat purrs. Yes I'm fun at parties.
@ritvikmath3 жыл бұрын
love it!
@teetanrobotics53632 жыл бұрын
Amazing content. Could you please order the playlist on your channel for beginners ?
@ankitranjan302 жыл бұрын
Thank you for the video, Ritvik! Not related to PCA but I was wondering if you could make a video on latent dirichlet allocation (lda) for topic modeling? It would be really helpful.
@Reivivus2 жыл бұрын
Liked and subscribed
@pickinnick1004 жыл бұрын
Frequency of purr =/= Amplitude of purr
@ajiths16894 жыл бұрын
great explanation
@HA-vh3ti3 жыл бұрын
How would you compare PCA vs Variable Selection/Regularization (Lasso/Ridge/Elastic Net), Is there any video comparing both?
@velevki2 жыл бұрын
We are saying that we are reducing the dimensions but each PCA is a linear combination of all the attributes. So how is this reducing dimension? This is the part I am not grasping.
@smudgepost Жыл бұрын
Very interesting thank you
@ritvikmath Жыл бұрын
Glad you enjoyed it
@smudgepost Жыл бұрын
@@ritvikmath I'm really enjoying your videos because it's giving me a working understanding of the mechanics under the hood. I've been toying with data science for years and struggled quite a bit, but with videos like this and the aid of AI bots to help (particularly with tracing errors), I'm learning so much faster today. As you get into great detail across the whole spectrum of machine learning I wondered if you had a video or might consider making one to show the structured approach to a machine learning project. Looking at the type of data the desired outcome and then piece-mealing all of the tools and approaches to the strategy. Each of your videos is very holistic, I would love to see one that was holistic for a whole machine learning project, without needing to re-explain the detailed concepts held in your other videos.
@tirthupadhyaya25193 жыл бұрын
You are awesome dude
@mirzaaghaalikhan1833 жыл бұрын
I was having a very bad day and this showed up! *Thanks KZfaq*
@davidcrawley94794 жыл бұрын
Terrific video by the way. Do you mean you loose a little bit of data or do you mean you loose a little bit of information? I am guessing that what you are saying is that you loose data without loosing information.
@beshosamir89782 жыл бұрын
how can i know, how much every PCA component capturing data ?
@sahil00942 жыл бұрын
how is dimensionality reduction & feature extraction different?
@iaaan12454 жыл бұрын
does PCA solve the issue of multicollinearity?
@theonionpirate10762 жыл бұрын
"A little messy, but it says 'feature extraction'." Agree to disagree.
@DeAdAnGeLTV4 жыл бұрын
You say your cat dataset has 3 Dimensions where as one could be left out because it has no great significance. I know it is a toy example but why wouldn't you just leave it out without calculating it with PCA?
@ritvikmath4 жыл бұрын
Great question. In this case when it is easy to visualize in 3d, we can just leave out that dimension. But, when the dimensions get higher and it get's harder to visualize you might consider PCA. The bigger reason is that sometimes the points all lie on a line or plane but that line or plane does not line up perfectly with the axes (one variable is a linear combination of others) so PCA is needed.
@user-bs8dc1dq1h3 ай бұрын
Imagine studying ONLY weights and lengths of cats for TEN years
@soufianebouabid29463 жыл бұрын
To all the ppl who care about cats HAHAHA nice one