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README.md

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@@ -7,7 +7,7 @@ Essential codes for jump-starting machine learning/data science with Python
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* Simple linear regression with t-statistic generation
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* Multiple ways to do linear regression in Python and their speed comparison ([check the article I wrote on freeCodeCamp] (https://medium.freecodecamp.org/data-science-with-python-8-ways-to-do-linear-regression-and-measure-their-speed-b5577d75f8b))
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* Multi-variate regression with regularization
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* Polynomial regression with how to use scikit-learn pipeline feature ([check the article I wrote on _Towards Data Science_](https://towardsdatascience.com/machine-learning-with-python-easy-and-robust-method-to-fit-nonlinear-data-19e8a1ddbd49))
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* Polynomial regression with how to use scikit-learn pipeline feature ([check the article I wrote on *Towards Data Science*](https://towardsdatascience.com/machine-learning-with-python-easy-and-robust-method-to-fit-nonlinear-data-19e8a1ddbd49))
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* Logistic regression/classification
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* _k_-nearest neighbor classification
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* Decision trees and Random Forest

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