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#probablisticprogramming search results

0xKrinza's profile picture. @zksync / prev. alt vm @fluentxyz, infra @ankr
krinza.eth
@0xKrinza
Dec 19, 2019

Markov chain's conditioning specifies that: "the future depends on the current state, but not past states." and, I'm living on this. #ProbablisticProgramming

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CWalshMD's profile picture. Associate Professor of Biomedical Informatics and Medicine at Vanderbilt. Focusing data analytics through a clinical lens (Views my own)
Colin Walsh
 @CWalshMD
Oct 24, 2018

@fonnesbeck a key advantage of probabilistic programming is that model specification is typically distinct from model fitting. Iteration is much easier as a result. @vumcdbmi #probablisticProgramming

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yangyaostanford's profile picture. Researcher and developer, a former reporter. 'Our world is a living expression of how we have and are using our minds.'
Yao Yang
 @yangyaostanford
Jul 23, 2020

Made my first Bayesian Model using #probablisticprogramming #PyMC3, it's more like an art than science! Anyone with experience in #probablisticprogramming? Would love to learn how you set priors!!!!

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DCivin's profile picture. Data scientist, AI @ meta. Coffee enthusiast, lousy surfer, noise rock enjoyer. Cambridge alum. opinions my own.
Damon Civin
 @DCivin
Dec 10, 2017

@yeewhye agrees: #probablisticprogramming needs to get to the point where it's easy for practitioners to exploit the structure in their problems. #MachineLearning vs #DataScience

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DataScienceDojo's profile picture. We make learning data science and LLMs easy! Join the community of 10,000+ professionals. #DSDojo
Data Science Dojo
@DataScienceDojo
Apr 17, 2021

🧠 This blog post provides a brief introduction to Probabilistic programming. hubs.ly/H0LmP2g0 #Probability #ProbablisticProgramming

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KartikThakore's profile picture. Partner @x_versal; Entrepreneur in Residence @ElevanceHealth.
Kartik Thakore
 @KartikThakore
Nov 8, 2022

If anyone is looking to do some bayesian modeling with pymc3 on mac M1 chips you will run into issues with numpy and blas. This might help #python #probablisticprogramming lnkd.in/giTNGwS5

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KartikThakore's profile picture. Partner @x_versal; Entrepreneur in Residence @ElevanceHealth.
Kartik Thakore
 @KartikThakore
Nov 8, 2022

If anyone is looking to do some bayesian modeling with pymc3 on mac M1 chips you will run into issues with numpy and blas. This might help #python #probablisticprogramming lnkd.in/giTNGwS5

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DataScienceDojo's profile picture. We make learning data science and LLMs easy! Join the community of 10,000+ professionals. #DSDojo
Data Science Dojo
@DataScienceDojo
Apr 17, 2021

🧠 This blog post provides a brief introduction to Probabilistic programming. hubs.ly/H0LmP2g0 #Probability #ProbablisticProgramming

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yangyaostanford's profile picture. Researcher and developer, a former reporter. 'Our world is a living expression of how we have and are using our minds.'
Yao Yang
 @yangyaostanford
Jul 23, 2020

Made my first Bayesian Model using #probablisticprogramming #PyMC3, it's more like an art than science! Anyone with experience in #probablisticprogramming? Would love to learn how you set priors!!!!

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0xKrinza's profile picture. @zksync / prev. alt vm @fluentxyz, infra @ankr
krinza.eth
@0xKrinza
Dec 19, 2019

Markov chain's conditioning specifies that: "the future depends on the current state, but not past states." and, I'm living on this. #ProbablisticProgramming

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0
1
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CWalshMD's profile picture. Associate Professor of Biomedical Informatics and Medicine at Vanderbilt. Focusing data analytics through a clinical lens (Views my own)
Colin Walsh
 @CWalshMD
Oct 24, 2018

@fonnesbeck a key advantage of probabilistic programming is that model specification is typically distinct from model fitting. Iteration is much easier as a result. @vumcdbmi #probablisticProgramming

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DCivin's profile picture. Data scientist, AI @ meta. Coffee enthusiast, lousy surfer, noise rock enjoyer. Cambridge alum. opinions my own.
Damon Civin
 @DCivin
Dec 10, 2017

@yeewhye agrees: #probablisticprogramming needs to get to the point where it's easy for practitioners to exploit the structure in their problems. #MachineLearning vs #DataScience

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