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README.md

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@@ -5,7 +5,7 @@ Essential codes for jump-starting machine learning/data science with Python
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### Tutorial-type notebooks covering regression, classification, clustering, and some basic neural network algorithms
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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](www.google.com))
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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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* Logistic regression/classification

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