Nice one! Also, a trivia: the Monte Carlo method was invented in the context of simulating card games (solitaire) in the computer. It's cool to see the method being used for playing cards!
Monte Carlo simulations are such a natural way to solve hard problems. It requires many fewer brain cells. And with the insane speed of CPUs (cheap computations) available today why would I pull out my old textbook on probability theory?
Hi! I absolutely loved the approach to them probelm and how easy you made Monte Carlo for me. Could you explain the KingKing algorithm you made please?
Hold on, so was the last Monte Carlo simulation inaccurate? I didn’t understand your point about that. There’s no way the true probability of that event was ~73%.
In python we use deepcopy when we want to make a new object with the properties of an existing object without creating a reference. If we use shallow copy then it just creates a reference. It's like pass by value vs pass by reference.
Since many of you were interested in the code, here it is...
github.com/Suji04/NormalizedNerd/blob/master/Miscellaneous/monte_carlo.py
Thanks a lot. Your way of explaining was amazing 👍
Nice one! Also, a trivia: the Monte Carlo method was invented in the context of simulating card games (solitaire) in the computer. It's cool to see the method being used for playing cards!
Yeah...From casino to nuclear weapons, the story of Monte Carlo is amazing!
"True random can only be found in nature": I'm thinking to the Creator that randomness is pseudo-random.
i call pseudo-random algorithms - pseudo-pseudo-random.
5:50 "It doesnt matter who comes first, the King or the Queen" 😂
XD
Sus
Monte Carlo simulations are such a natural way to solve hard problems. It requires many fewer brain cells. And with the insane speed of CPUs (cheap computations) available today why would I pull out my old textbook on probability theory?
Great video! Can you cover Markov Chain Monte Carlo as well in a future video?
Great suggestion! I'll definitely give this a try
2:15 that mad me laugh. "subtracting this bad boy"
Haha XD
Nothing tops what he said later, no double entendre intended: "It doesn't matter who comes first--the king or the queen."
This is awfully similar to 3Blue1Brown videos, the animations and the colors used...
Because I'm using manim, an open source Python library created by Grant himself
@@NormalizedNerd Awesome !
0:20 fart noises
May I ask which tool do you use to make this moving x,y space/graph? Thanks in advance.
I used a python library named Manim :)
0:24 me in the mornig after a coffee and a sigarette
Hi! I absolutely loved the approach to them probelm and how easy you made Monte Carlo for me. Could you explain the KingKing algorithm you made please?
Hello thank you for your video. But I do not know what does 49P4 mean in 1:54. Could you help me explain this?
Hold on, so was the last Monte Carlo simulation inaccurate? I didn’t understand your point about that. There’s no way the true probability of that event was ~73%.
Thank you, I understand the main subject but couldn’t really understand the codes. I’ll try by my own.
My brain exploded when you've said "easy, right?" 🤯
great Polish math do that Stanisław Ulam
en.wikipedia.org/wiki/Monte_Carlo_method
we study it in secondary school
Please make a video on Markov Model
I definitely will!
first time I actually understood Monte carlo simulation. Thanks for the video
i didn't understand how you shuffled the deck with random data points if you can't obtain randomness?
Best definition of monte-carlo method imo is: instead of predicting, let it happen
Thanks mate!
The bell sound in the beginning is way too loud for my taste :)
Feedback noted.
Great video! I really liked it. I subscribe for more content!
Awesome, thank you!
first time I understand clearly what MC is lol thank you !
Great work
👏👏👏👍👍👍👍👏👏👍👍👍👍
Really great explanation and motivation why using Monto Carlo. Thanks
Easy right? 😂. Love this guy.
Hey, man, that's thing is real cool! Keep doing great videos, love graphs, simulations in your videos, real good!
fantastic video
Thanks bhai❤
just live it..........
Awesome
Very great video
great video, thanks
Great vid ! Subscribed !
in 1.44 how does it become 49 positions?i thought it was supposed to be 48
I get it finally,thanks!
where can i find the whole python code please?
Finally uploaded the code to GitHub...
github.com/Suji04/NormalizedNerd/blob/master/Miscellaneous/monte_carlo.py
Thanks for waiting :)
What the heck is copy.deepcopy?
In python we use deepcopy when we want to make a new object with the properties of an existing object without creating a reference. If we use shallow copy then it just creates a reference. It's like pass by value vs pass by reference.
Thank you so much sir !
make a game... how much of the viewers have stoped to calculate it by their own? I would say 2
Haha XD
@@NormalizedNerd but thx for that great video.. now i know how that works
Really awesome!! Keep up the great work!
Thank you! Will do!
Well done!
Great demo!
Absolutely loved this 👏
you saved my life :) ıt is amazing explanation
Thanks!
Hi do you have the link for the python code notebook? Thanks :)
I haven't made it public yet...I'll add the link in video description.
@@NormalizedNerd hello there! where can i find it?
Thank you so much! Great explanation.
You're very welcome!
Best Monte Carlos video on youtube!!
Glad you think so ❤️
Ads noce😎😎
Finally... -_-" :D
Great content，Great teacher!
Thank you! 😃
Keep it up!
I will!