Coding MCMC : Data Science Code

Coding Accept-Reject, Metropolis, and talking about the tradeoffs!

[xxshogunflames]

Man you blow these videos out of the park, it’s like surreal how good these videos are at tying the big picture together. Thank you for the content!!!

[MrSystemoutprintln]

These MCMC videos (and of course others too) are just brilliant, can't thank you enough!

[achimkeks]

Love your videos! Great balance between simple explanations and giving a good overview of the topic.

[gajrajsingh]

How to get this norm constant ? At 1:32 integration was from 0 to inf and -inf to 0, while function definition was for x>=1 ?

[bryanshi]

For the wolfram integral, I think it should be "for x from 1 to infinity".

[Joy_SR]

Why ">> if np.random.random() < prop " (at 10:43), the sample is accepted? what is the role of "np.random.random()" here?
Thank you!

[orjihvy]

In practice, you have observation data. Can you look at a video of how to use data with MCMC?

[SameenIslam]

Really cool, it would be great if you could cover Sequential Importance Sampling (SIS) too.

[Afewwilliams]

These vids are excellent, thanks a lot

[sharmilakarumuri]

Please can you do a video on hamiltonian monte carlo

[changkaizhao]

10:43 in cell 48, why use f(candidate)/f(samples) as recept ratio? Where are the transition terms according to mcmc?

[laxmividyaclasses]

For likelihood, we have pareto distribution, and for theta prior follows Gamma distribution. We have 20 samples given . Now my posterior is complex, involving sum of logxi. What proposal density should i use and for sum logxi appeared with theta in posterior should i sum all data given what to do and how to proceed could you help

[salenatorresashton]

You do a great job with your Code with Me Videos. I'd like to refer students to your videos-- do you plan to make more of these?

[orjihvy]

Is f(x) always greater than p(x) given the normalizing constant?

[seyyidemre]

The code in cell# 49 will always give 99.9% accuracy. Is it not better to subtract 1000 from n_accept and report that instead? The size of the retained_sample will always be 1 million as you append a new value whether you accept or not.

[orjihvy]

Why is that a drawback, that samples are correlated? Isn’t that the entire point behind MCMC?

[leonardofacchin]

The fact that the sample draws are correletated in the Metropolis (and especially in the more efficient Hamiltonian MonteCarlo) algorithm looks like a feature to me rather than an unfortunate necessity. It's what allows the algorithm to be efficient. As long as the final proportion of sample draws closely matches the posterior density, how the samples were obtained seems to be much less important. The samples are correlated because these algorithms are actually built to explore the sample space in a smart manner.

[UsmanKhan-xshz]

how can MCMC be used in the realm of stocks and finance? I’ve been looking into making a stockbot as a personal project and landed on MCMC as a viable option

[datorusfinance]

What's so bad about the correlation in the Metropolis-Hastings method?

[kmshraddha]

What is difference between tuning parameter and standard deviation and where to use which?