Naive Bayes belongs to the family of probabilistic algorithms that take advantage of Probability Theory and Bayes Theorem to predict the class. Let's learn how it works!!
Read moreIn supervised machine learning, we are building predictive models that predict variance of some variable, using variance of some other variables. To model these connections, we have to learn Conditional Probabilities and Independence of events.
Read moreLinear Regression is one the most basic algorithm on ML. With the likes of sklearn providing an off the shelf implementation of Linear Regression, it is very difficult to gain an insight on what really happens under the hood. This tutorial is aimed at implementing Linear Regression from scratch in python using Numpy.
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