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Logistic regression is a very robust machine learning technique which can be used in three modes: binary, multinomial and ordinal. We talk about assumptions and some misconceptions. For example, people believe that because logistic regression fits only a linear separator in the expanded dimensional…
In this episode with talk about regularization, an effective technique to deal with overfitting by reducing the variance of the model. Two techniques are introduced: ridge regression and lasso. The latter one is effectively a feature selection algorithm. 
In this episode I will try to convince you that Linear Regression is one of the most powerful Machine Learning algorithms. We will talk about common misconceptions, especially that Linear Regression is not able to model non-linear relationships. We also discuss how the myth of normality encourages …
We talk about the importance of inferential statistics in Data Science. Inferential statistics are a set of techniques used to make generalizations about a population from a sample. One of the tools used in inferential statistics is hypothesis testing. In this episode we provide a couple of example…
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