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Linear Regression With Maximum Likelihood Estimation (Tutorial 2)

Difficulty level
Beginner
Speaker

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
Prerequisites

Experience with Python Programming Language

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