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##### Activity
chen wei
@auroua
I am study gibbs sampling method recently, I can't understand how to sample from p(x1|x2, x3)
Thomas Wiecki
@twiecki
do you have a specific example?
chen wei
@auroua
Does sample from this conditional distribution is easier to directly sample from the joint distribution
Thomas Wiecki
@twiecki
yes, exactly
this is for cases where you can't sample directly from the joint distribution
chen wei
@auroua
if the dim is very high
Thomas Wiecki
@twiecki
there are also many very simple models where you can't do it directly
chen wei
@auroua
I saw a example about two-dim gaussian distribution
How does the software implement about samples from a gaussian distribution
Thomas Wiecki
@twiecki
there's a great book called "Doing Bayesian Data Analysis"
that goes through it
chen wei
@auroua
I am reading pattern recognize and machine learning
In chapter 11
This book give a simple method
first generate a random number from uniform distribution over the interval (0, 1)
and then use a equation to caculae the result, and the result is from a gaussian distribution
Does the software implement in this way?
Thomas Wiecki
@twiecki
that sounds more like importance sampling
we don't implement that
chen wei
@auroua
It's not important sampling
Thomas Wiecki
@twiecki
that describes it all
and also what and how we implement it
chen wei
@auroua
importantance sampling caculate the expetations
Ok thanks
chen wei
@auroua
@twiecki hello
I read another article "Bayesian Deep Learning"
Does the bayesian deep learning just means using variational inference method to approximation the poster distribution of the weights in the neural network?
But how could I know this method is better than the traditional deep learning training method like using SGD to find the best weights?
Thomas Wiecki
@twiecki
we don't know that yet
chen wei
@auroua
@twiecki thanks
you blog is excellent!
thanks
sushmit-staples
@sushmit-staples
@twiecki
@twiecki Has anybody tried porting the programs for second edition?
@aloctavodia ^^^
Osvaldo Martin
@aloctavodia
@sushmit-staples you may want to check https://github.com/JWarmenhoven/DBDA-python I understand is not complete, but I think is a good place to start.
sushmit-staples
@sushmit-staples
@aloctavodia Thanks so much
I was thinking to port the second edition exercises in python
Thomas Wiecki
@twiecki
@sushmit-staples I'm sure @Jwarmenhoven appreciates help
Osvaldo Martin
@aloctavodia
Yeah! It seems he is the only one contributing code :-(
sushmit-staples
@sushmit-staples
I will try to add materials to it, if stuck with anything will use this forum for help :)
fbparis
@fbparis
Hello all :)
I have a naive question about models: in every tutorials I’ve read they study a simple problem where they can graph the datas in 2D or 3D and then guess a model to try
But what if there are too much dimensions and you can’t graph anything to visualize the datas
also i was wondering if the process of finding a model from datas can be automated
Osvaldo Martin
@aloctavodia