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Latest Resources in Bayesian Analysis

Bayesian Analysis

How to Implement Bayesian Optimization from Scratch in Python machinelearningmastery.com

Published October 14, 2019 under Machine Learning

Bayesian Optimization provides a principled technique based on Bayes Theorem to direct a search of a global optimization problem that is efficient and effective. It works by building a probabilistic model of the objective function, called the surrogate function, that is then searched efficiently with an acquisition function before candidate samples are chosen for evaluation on the real objective function.

Bayesian Analysis, Python

Hands On Bayesian Statistics with Python, PyMC3 & ArviZ towardsdatascience.com

Published July 28, 2019 under Statistics

If you think Bayes’ theorem is counter-intuitive and Bayesian statistics, which builds upon Baye’s theorem, can be very hard to understand. I am with you.

There are countless reasons why we should learn Bayesian statistics, in particular, Bayesian statistics is emerging as a powerful framework to express and understand next-generation deep neural networks.

Bayesian Analysis, Pymc3, Python

Kalman and Bayesian Filters in Python github.com

Published April 17, 2019 under Data Science

Bayesian Analysis, Kalman Filter

Estimating Probabilities with Bayesian Modeling in Python

Published December 6, 2018 under Data Science

Bayesian Analysis, Pymc3, Python

Cookbook – Bayesian Modeling with PyMC3 eigenfoo.xyz

Published June 22, 2018 under Machine Learning

Bayesian Analysis, Pymc3, Python

Computational Methods in Bayesian Analysis plot.ly

Published June 25, 2015 under Machine Learning

Bayesian Analysis, Machine Learning, Python

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