#1. Q Learning Algorithm Solved Example | Reinforcement Learning | Machine Learning by Mahesh Huddar

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#1. Q Learning Algorithm Solved Example | Reinforcement Learning | Machine Learning by Mahesh Huddar

The following concepts are discussed:
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Q learning algorithm,
q learning algorithm in machine learning,
q learning in reinforcement learning,
reinforcement learning,
reinforcement learning solved example,
solved example q learning,
q learning numerical example
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Mahesh, you're just too good!! Super well explained. Thanks for the help!

angelgarcialopezdeharo
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Nice Explanation ... Is it possible for you to explain inverse reinforcement learning with similar example where we have to compute reward function from expert?

hardikrajeswaran
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Very nice explanation, because, unlike the explanations I have seen so far, you run through the algorithm, showing the Q learning process. Thanks a lot!

marcods
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This is one of the best youtube channel in terms of Machine Learning, I watched a lot of foreign videos, but no good explanation, i just watched this video for 5 minutes understood everything, Thanks for your help

VedantPratik
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Thank you sir, it's the best explanation for q-learning.

poojithsrisai
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sir, this is helpful.
Any reasons you had taken -1 and 0; instead of 0 and 1 for the values in the matrix?

ganeshsubramanian
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thanks alot! learned alot in just 11 minutes!!!

junaid
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Thank You very much it helped me a lot Very Nice Explanation...

kiranmaik
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Very good job, Thanks a lot for ur efforts

kenzakhelkhal
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Great video! All others ignore the technical aspect but you went ahead and

Macooasme
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Will every one get the same final value as yours irrespective of the random selection they take or will change?

topinfo
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Very good exlaination of example. How to implement this in MATLAB or Python? are there ready codes available?

shabbirbohra
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do I calculate that Q(3, 2) is equal to 0, and how do I calculate 51?

andrewhyc
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Thank you! Excellent explanation and very helpful..

robert-dr
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how did u get 51 and 64 as values shd have explained those as well

NHAIushaprakki