IBM Technology

1,750,000 subscribers

⏱ 👁 91,942 views

Principal Component Analysis (PCA) Explained: Simplify Complex Data for Machine Learning

Video Overview & Insights

Fit for purpose data store for AI workloads → https://ibm.biz/BdmLTX

“

That's a good intro - appreciate it.

— @MagicTortoise-h4d

Discover how Principal Component Analysis (PCA) can simplify complex data sets and improve your machine learning models. In this video, we break down PCA, a powerful technique for reducing data dimensions while retaining crucial information. Learn how PCA helps in risk management, data visualization, and noise filtering, and see real-world examples of its applications in finance and healthcare. Whether you're a data scientist or a machine learning enthusiast, this guide will help you understand and apply PCA effectively.

AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdmL37

“

Very nice explanation

— @kevinzebb

More User Perspectives

😂😂😂😂😂❤❤❤❤❤😂😂😂😢😢😢😮

@WendyRoodal

Crazyyy❤

@kaushiki.sharma

It's worth remembering the following if you'll be feeding the compressed data into a logistic regression model: if most of the discriminative ability of the data lies along a low-variance dimension, then the compressed data may no longer possess that part of the data that is most useful for classification. PCA is an unsupervised method, remember.

@ryanj748

Briliiant job!!

@rjvtggr

IBM on YT is amazing and IBM on coursera.. i wish i could say same. pls update those lectures as well. will be thankful to u.

@nssandhu4401

Thank you so much for the video. Question. How did you write on a seamingly glass screen and record. What did you use?

@samanthapikus3178

I went through a book with many examples to understand PCA, and you explained everything so concisely in an 8-minute video. Thank You!

@manvirkaur1383

Where is the part Explaining "How PCA does that?"

@zaintechtips

Couldn’t fully agree here. I break down why in my own content.

@CRYPTOTRADERPO

You are the man! Very clear explanation. You are a great presenter who explains abstract concept in simple language. Thank you for the IBM team effort!

@karenlwk

Brilliant! Perfectly explained! Keep it the good work!

@fredericoamigo

You've taught me so much about brewing. Now, as a developer, I'm diving into data science — and look who it is! I owe you a lot for all the amazing educational content you've shared with the world.

@Patrickae12

I saw it in x0.75 and I understood it. You were bit fast in this video

@saisrikaranpulluri1472

brillliant

@brahman4338

Thank you

@RenalusDieumarthe

The screeching sound is a huge turn off tbh. Wouldn't mind that sound in lecture hall but in utube video, it's too loud.

@ShaharulYahya

Thank you for the clear and concise explanation. How can you deconstruct a PC into its components?

@DrT8039

So good❤

@aimaker

What’s with all the names in the chat? Is a prof using this video as attendance 😂😅

@zbady4595

Williams Jessica Williams George Perez Jeffrey

@FaradayDave-x2s

Williams Jose Taylor Jessica Jackson Jose

@celiafeconors216

how are you writing on the glass?

@ishankinger9647

Please do not use a marker on a glass, the noise is torture

@hongyusun5092

This guy also happens to make superb craft beer!

@paolobagares2522

Anderson Jeffrey Lewis Richard Harris Donald

@NancyMendozai

can you use pca for likert scale data

@josephtaanyan6162

you saved me in my academy work, thanks! (i'm using it with clustering)

@natan.mendes

Thank you for introducing this topic. I appreciate how your videos provide an overview of various ML methods.
As a suggestion for future videos, I would like to recommend one covering the principles of Independent Component Analysis (ICA).
This method has recently been in high demand in my projects.
Cheers!!!

@vitorribeirosa

👍 from India

@mdrehan4all

Explanation is fine but if you could come up with a video relying more on visualization of PC1 and PC2 then it would be great. Thanks.

@ZirghamIlyas

This sounds a lot like Dimentionality reduction in Unsupervised learning. Newbie here, Is that right?

@Codetutor-DemystifyCoding

Imagine not understanding neural nets and using Ai or math other people came up with to remove factors that are calculable from other factors 😂

@ValidatingUsername

Great Video! I am a ds in a financial institution.

@juanhe3430

thanks for this, awaiting for many more similar to come!

@ashraf_isb

INTERESTING.😀👍🏾

@tyrojames9937

thank you, great topic with easy understanding explanation

@mjacfardk

#IBM #IBM Cloud