Linear Regression With Maximum Likelihood Estimation (Tutorial 2)
Linear Regression With Maximum Likelihood Estimation (Tutorial 2)
In this tutorial, we will use a different approach to fit linear models that incorporates the random 'noise' in our data.
Topics covered in this lesson
- Learn about probability distributions and probabilistic models
- Learn how to calculate the likelihood of our model parameters
- Learn how to implement the maximum likelihood estimator, to find the model parameter with the maximum likelihood
External Links
Prerequisites
Experience with Python Programming Language
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