Markov Chains: Recurrence, Irreducibility, Classes | Part - 2

Let's understand Markov chains and its properties. In this video, I've discussed recurrent states, reducibility, and communicative classes.
#markovchain #datascience #statistics

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[abhishekarora]

why this video has views only on thousands? it needs to be in millions!

[Arjunsiva]

Great to see high-quality educational channels like 3Blue1Brown coming from India. Btw, what software do you use to create the animations?

[yiyiyan]

This is really nice for the beginners to understand the basic properties of markov chain. It would be great if your video could go further to the hidden markov chain and factorial markov chain:)

[nicolasrodrigo]

You are a very good math professor, thanks a lot!

[jayeshpatil]

Can't believe that Indian is at it's prime. Ek number explanation 🔥🔥🔥

[iglesiaszorro]

Very catchy! I request you to make more such videos on markov chains with these kinds of awesome representations!! Markov chains were a dread to me previously.. your videos are too cool!

[Mithu]

Very good precised explanation with nice animation. Thank you for your video. Please make more for solving numericals and implementation of practical scenario.

[tristanlouthrobins]

Absolutely brilliant, clear explanation!

[harishsuthar]

Looks like Stat Quest Channel BAM!!!
Clearly Explained!!!

[georgemavran]

Amazing explanation! Can you also please explain the periodicity of a state in a Markov chain?

[olesiaaltynbaeva]

Your channel is a great resource! Thanks!

[ianbowen]

5:46 – "Between any of these classes, we can always go from one state to the other." But how can we do that if two of the classes are self-contained? Do you mean that we can always move between states within each class?

[amritayushman]

Thanks for the videos. Helped me a lot. Would appreciate if you upload a video for complete in depth mathematical analysis of the Marco chain and its stationary probability.

[Garrick]

Bro we need more videos. Don't wait for comments just do it 🙏🙏❤❤

[wonseoklee]

Thanks for the video. Now I can understand whenever I hear Markov chain!

[amarparajuli]

Amazing content for ML and Data Science people. Keep up Bro. Will share it with my ML comrades.

[jingyingsophie]

I don't quite understand the part where 2 is also a recurrent state in the first example. If the definition of the recurrent state is where the probability of returning back to that state is =1 (i.e. guaranteed), wouldn't 2 be a transient state since there is the possible case where 1 goes back to itself only ad infinitum?

[kirananumalla]

Very clearly explained! Yes would be useful if there are more videos..

[hansheytens]

Hello, dumb question. Shouldn't state 2be transient also. I mean, there is a extremely small chance (but not zero), that in a random walk we go from state 2 to state 1 and then we keep looping through state 1 forever, hence not coming back to state 2? No? Thanks love your vids.

[preritgoyal]

Great brother 👌👌

So, if the stationary distribution has all non zero values, the chain will be irreducible ?
(Since all states can communicate with each other)

And Reducible if any of the states has 0 value in stationary distribution ?