Machine Learning Tutorial Python - 19: Principal Component Analysis (PCA) with Python Code

PCA or principal component analysis is a dimensionality reduction technique that can help us reduce dimensions of dataset that we use in machine learning for training. It helps with famous dimensionality curse problem. In this video we will understand what PCA is all about, write python code for handwritten digits dataset classification and then use PCA to train the same model using PCA.

⭐️ Timestamps ⭐️
00:00 Theory
09:12 Coding
23:04 Exercise

#️⃣ Social Media #️⃣

❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

[rakeshbullet]

Awesome videos - Simple explanations. A balanced approach to teaching with a right mixture of theory and practicals and not overwhelming the learners . i loved the approach - After seeing numerous ML training videos from across the spectrum, this is far most the best one i have seen . Thank you for taking time to create these videos .

[mayishamaliha]

super helpful for newbies not scaring them off with too many statistical terms and getting overwhelmed. thank u so much

[dushyyanta]

You are the best! I am doing PG in DS but still, I watch your videos for better understanding. Kudos! Keep it up!

[mohitupadhayay]

The last few minutes were BANG ON! This is what i wanted to hear. Thanks!

[Rainbow-ljpp]

This is a really easy to understand and thorough explanation of principal component analysis. Many others I watched were either too technical and math theory oriented or to basic in showing how to use the function but not what it does. This is a great balance of understanding and practicality.

[bhaskarg]

Thank you, PCA concept is clearly explained .
Need to understand in actual real life scenarios, what we consider, the performance or process time

[TK-fxdh]

My long await topic!!!! Thank you for posting this PCA lesson

[prakashkoneti]

I would really appreciate for your hard work in making these videos and decoding the complex to easy..

[K.Charz]

Thanks sir the great work, your explanation makes ML easier for sure 🙏

[luciamatamorospava]

it's like the 10th video i'm watching on PCA and the FIRST one I understand, thank you so much!

[akinloluwababalola]

Hello Code basics. I usually enjoy your videos as I learn a lot from them. Can you make a video on association rules, apriori algorithms and any machine model that deals with the determination of interrelationships amongst variables? Thank you

[jinks]

Another very informative video.
DHANYAVAAD ! :)

[dees]

great explanation on PCA. It's an abstract concept to grasp. well done

[mukeshkumaryadav]

It was an amazing explanation of PCA without much mathematics and eigen value and vector which scares me. Interesting learning 1. we can know variance explained by each PC which helps.

[boogersincoffee]

I've been struggling to understand this and this cleared everything up, thank you

[guillermokinderman]

I was trying to understand PCA, this video helped me a lot

[Maniclout]

Amazing explanation, I understand PCA now.

[mansijswarnkar]

Wonderful, as always - thanks for making this video, it has helped me a lot ! Regards

[yvibsod]

Masters in Data Science in the UK and still loves watching only your videos :-)

[leamon]

Thanks for this amazing tutorial. Hope you could do one video about when to use feature selection and feature extraction, or even combination of them.