Perhaps you could do a short series just on how well MCMC generalizes. There's potential for projects in physics, chemistry, biology, astronomy, ecology, medicine, risk assessment, or even sports! It could even help to broaden the channel's audience!
25:00 Is it ok to use fibonacci sequence for the cumulative particles? If so, then we could also use the differences between the fibonacci numbers to determine how many E's to sum up to get the total energy deposited for each 10s interval.
For anyone still interested in the numerical inverse, I'd like to propose another way: ``` x = np.linspace(0,2,100) f = x**2 f_inv = np.interp(x,f,x) ``` This is very similar to just plotting x over y using pyplot or something similar, using linear interpolation to sample between points instead of integer indezes as proposed in this video.
Nice video, I was wondering if you could make a video on calculating the maximum likelihood estimate, Fisher information and CRLB then that'd be great!
it is very nice and helpful video. I have a question and hope you can reply. how can we get the distribution function(like,f(x) ) for MC to do the simulation of experiment? it is from previous experiment or specific theory? Thank you very much
@@MrPSolver May I venture to ask in your future videos, could you delve more into machine learning or pricing of derivative instruments, cos' these are the areas I'm interested in. Your current batch of videos are fantastic, you've taught me so much about Python beyond the basics and with practical applications. I've already subscribed your channel and hit the bell notification icon. Heaps of thanks !!!
Monte Carlo simulation in Python with Mr. P Solver... Man, you made my day!
Perhaps you could do a short series just on how well MCMC generalizes. There's potential for projects in physics, chemistry, biology, astronomy, ecology, medicine, risk assessment, or even sports! It could even help to broaden the channel's audience!
One of my greatest love is monte carlo methods, ill watch this when i have some time, nice work.
My new favourite RUclipsr!
Super informative, thanks for the time and effort you spend on these videos!
25:00 Is it ok to use fibonacci sequence for the cumulative particles? If so, then we could also use the differences between the fibonacci numbers to determine how many E's to sum up to get the total energy deposited for each 10s interval.
Please make one more video on this using data, this is the best tutorial.
I am in love w ur channel as an applied math major
This so far is the best MC theory+implementation i have ever seen! Thanks for doing this I am looking forward to something on Autoencoders 😀
For anyone still interested in the numerical inverse, I'd like to propose another way:
```
x = np.linspace(0,2,100)
f = x**2
f_inv = np.interp(x,f,x)
```
This is very similar to just plotting x over y using pyplot or something similar, using linear interpolation to sample between points instead of integer indezes as proposed in this video.
Nice video, I was wondering if you could make a video on calculating the maximum likelihood estimate, Fisher information and CRLB then that'd be great!
man how do i get that nice style package?? its not included in matplotlib it seems
This channel is underrated 🙌🏻
Is your method of generating a distribution different then the metropolis method or is that what it is?
How to choose those parameters included in function?
Thanks for it offers
A question what the name of logical u present with him
it is very nice and helpful video. I have a question and hope you can reply. how can we get the distribution function(like,f(x) ) for MC to do the simulation of experiment? it is from previous experiment or specific theory? Thank you very much
I've learned alot from ya, keep it up ! I look forward to your next video. Thank you.
Next video gonna be deriving the Boltzmann temperature distribution through a simulation of colliding particles. Should be up next Monday or Tuesday!
@@MrPSolver May I venture to ask in your future videos, could you delve more into machine learning or pricing of derivative instruments, cos' these are the areas I'm interested in. Your current batch of videos are fantastic, you've taught me so much about Python beyond the basics and with practical applications. I've already subscribed your channel and hit the bell notification icon. Heaps of thanks !!!
I would love to do a monte carlo simulation running on a web server. Do u have an idea how to do so?
Mind sharing your thesis?
Boy! really good stuff!! loved it!! thanks a bunch!
U don't mention it is CDF technical in part one also known as change of variable
Thank you a lot for this amazing explanation! I always learn a lot from you.
Amazing explanation....!!!!🔥🔥🔥😃😃
But where is the RAP song...?? BRO.
I miss it...😔
can you help solving a similar code?
Finally found hidden gems
Your videos are great 🙌 . Can you make a video on how to start with python and become good at it for complete beginners
Gracias por el vídeo! Me ayudó mucho a entender mejor el método(:
Nice video man , really wow
Really cool, thanks a lot for your great work
Will you make a video about navier stokes or how to simulate a fluid ? Would be very interesting
Your channel is great for me.beacuse I am a mechanical engineering student.
Can i know your age
Brilliant! 🙏🏽 Thank you
Loved it! Love you!
Thank you so much for your vid - I've learn t a lot!🙂
very good !!!
Thank you, Sir
Wow! This shit is gold. Cheers dude
Amazing!!!
love this. Good job
800th liker 😁
It hurts when he talks? He is always grimacing.