I love this being part of an introductory Linear Algebra series. I‘be seen many non-mathematicians coming away from LA thinking it is pretty useless in the real world. But here we have some of the more nuanced basics applied beautifully in a real world example. Love it. Diagonalisation, Limits, Eigenvalues and Eigenvectors all motivated in one easy to understand example.
I know Markov Processes as Stochastic Processes with Markov Property and Countable (not necessarily finite) State Space (which is not so nice for Diagonalisation… and must sometimes be solved with difference equations…), but I guess this is a matter of opinion / definition etc. ^^ and here the finite one is definitely what we want…
In first example (puppy sum) u directly done using AXo,AX1,AX2 but in second sum u done AXo using eigen values diagonalzation method Here my question is in second question can we do directly AXo with out finding eigen value and all
I love this being part of an introductory Linear Algebra series.
I‘be seen many non-mathematicians coming away from LA thinking it is pretty useless in the real world. But here we have some of the more nuanced basics applied beautifully in a real world example.
Love it. Diagonalisation, Limits, Eigenvalues and Eigenvectors all motivated in one easy to understand example.
I know Markov Processes as Stochastic Processes with Markov Property and Countable (not necessarily finite) State Space (which is not so nice for Diagonalisation… and must sometimes be solved with difference equations…), but I guess this is a matter of opinion / definition etc. ^^ and here the finite one is definitely what we want…
How to calculate the second year
You multiply the x_0 vector with the transition matrix twice.
Based. Haha half a semester course in a 16min video. Clearly explained. Thanks
Topic clearly explained! I particularly like your examples and step-by-step details.
Thanks for watching!
Excellent explanation and examples
Glad it was helpful
Awesome explanation of Markov process/chains. Thank you so much! Just subscribed!
I'm glad this helped!
Nice work. Thanks.
Thanks for watching!
What if x isn't diagonalisble
Thanks ,It helped a lot..
Glad it helped! Remember to subscribe!
Only now I understand the mark of chain
sum of each row in trasition matrix should equal 1 ??
For the matrix to represent a stochastic process, the columns must add to one.
can we do like directly Ax0 instead of find e.values and vector
Hi! I'm not sure what you mean here. Can you explain your question a little more?
In first example (puppy sum) u directly done using AXo,AX1,AX2 but in second sum u done AXo using eigen values diagonalzation method
Here my question is in second question can we do directly AXo with out finding eigen value and all
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