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Using the Maximum Likelihood Estimation (MLE) to determine a linear line of best fit to noisy data

Date Fri 21 June 2019 Modified Fri 21 June 2019 Tags python / MLE / linear model / regression

This post shows a simple derivation of the likelihood equation, how we can maximise likelihood to determine a line of best fit with Python and how this compares to Ordinary Least Squares (OLS).

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About Dan Humphreys
Hello and welcome to my blog. I'm a Chartered Mechanical Engineer and budding data scientist based in Hull, Yorkshire, UK.

Currently open to work enquiries and contactable via email or through one of the social media outlets below.

As of August 2020 I am also now a certified entry level Python programmer.

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