Learn the concepts behind Bayesian statistical modeling with PyMC3
Compare and contrast the frequentist and the Bayesian inference approaches
Exercise Statement
Compare the stochastic gradient based frequentist's method vs. probabilistic Bayesian method to solve a simple linear regression problem and interpret and contrast the outcomes from both the approaches.
Prerequisites
Basic knowledge about linear regression (#43)
Basic knowledge of Bayesian approach to probability
Data source/summary:
This comparison can be performed on a simulated data generated through _sklearn.makeregression function.
(Optional) Further Links/Credits to Relevant Resources:
Learning Goals
Exercise Statement
Compare the stochastic gradient based frequentist's method vs. probabilistic Bayesian method to solve a simple linear regression problem and interpret and contrast the outcomes from both the approaches.
Prerequisites
Data source/summary:
This comparison can be performed on a simulated data generated through _sklearn.makeregression function.
(Optional) Further Links/Credits to Relevant Resources:
https://docs.pymc.io/