Great collection of videos, Thoroughly loved it..

You just cleared every doubts on this topic, it's 10 days before my exam watching your video and getting everything cleared

why does the covariance matrix rotates the vectors towards the greatest variance?

great explanation, simple and visualized. Thanks! =)

THANKS, you've answered a lot of questions in my mind with your amazing explanation!!!!

you sound like Gale Boetticher from breaking bad

This video has (by far) the highest knowledge/time of any other video on this topic on RU-vid. Clear explanation of the math and the iterative method, along with analogy to the simpler algorithm (k-means). Thanks Victor!

Content is good, but please amplify audio.

When andrew tate explaining Math

sir we cant see your cursor omg

how to know the value of P(b) and P(a)

Excellent explanation

ty

Its amazing this works at all, because the first step is to take a 2d image that makes sense, into a 1d image that has lost ALL spatial information. A 1d stream of pixels is not an image.

Splendid. Example very well portrays the algorithm stepwise!

Thanks for this. Your video helped bring clarity to the problem statement.

but is not projection (y .e)e where y = x - mew

at 3:08 the variance estimator shoud be divided by (nb-1) as corrected estimation and not nb .. that's what we call Bessel's correction

Great tutorial! But why the slop of two eigenvectors are expected to be the same?!

Outstanding!

thanks brother

Great Explanation Sir. I don't know why it motivated me to appreciate and comment on the video.

Andrew Tate of machine learning

This course / lecture series has been staggeringly useful, thank you. It was also explained in a way that I could understand easily - and I have been struggling with the eplanations from others. You simplified things superbly. I did get lost when we started talking about mathmatical functions et al, but the information I needed was more to do with concepts and ideas - so i could safely let the maths part slip by, though noting different efficiencies of course. Thank you. Sincerely appreciate you sharing your work.

Amazing, thank you!

Enlightening, thank you!

Thanks so much! I will refer my students to your webpage!

This is awesome explanation. Thanks !

Studying at TUM. I admire german students who are following the lecture contents from the uni. Taking ML course atm, but here, the lecture is just like dumping only the whole concepts, regardless of whether students can understand them or not... So nice explanations in every video in ML related playlist.. I fcking regret that I did not choose the UK to study my master's.

Wow, you explain very well, thank you! I was having a hard time understanding my professor's explanation in our class.

Thanks for posting these Victor. I'm working on understanding the prior bias of precision and this helped. I hope things are going well!

Great tutorial!

Incredibly insightful! Your teaching style, peppered with examples, made complex topics like inverted index data structure and MapReduce algorithms easy to grasp. The way you broke down the compression techniques was particularly eye-opening, and I gained a newfound appreciation for the mechanics behind large-scale search engines and big data management. Before watching your lectures, I was quite overwhelmed by these concepts. However, your clear and structured approach has removed that uncertainty and replaced it with genuine interest and understanding. Thank you for your dedication to spreading knowledge. Your work has had a significant impact on my learning journey, and I am truly grateful for that. Please continue to share your wisdom; you are making a real difference in the lives of your viewers!

how do we block the japanese hack

andrew tate?

Thankyou😃

Step 1 is center, should we also scale so variance = 1

Hi sir is k means and kneighborhood algorithms are same ?

Great playlist.

This is the first time that PCA has actually made sense mathematically. Great video

I cant help but notice the middle dotted line looks like a logistic regression curve. I should know this.. But is there any relation?

Sounds just like Andrew Tate

As mentioned by @omidmo7554, I was exactly in a similar situation. you have explained it so lucidly. Thank you so much Victor!

SVD 3:08

Great Explination

O chatgpt me mandou aqui 😳

Amazing video, perfectly explained the concepts without getting bogged down in the math/technical details.

Andrew Tate?

Great explanation mate, thanks!

incredible explanation!