A Receiver Operating Characteristics (ROC) Curve is used to describe the trade-off between correct classifications and wrong classifications. The ROC curve displays a plot of the True Positive (TP) against …
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I’m providing set to data science question and answers. The answers would be clear and brief for anyone to understand no matter your field. However, if you would like to …
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This tutorial would cover Exploratory Factor Analysis. We would cover the following sub-topics: What is Factor Analysis(FA) Difference between Exploratory FA and Confirmatory FA Application of Factor Analysis Steps of …
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I will try to explain Likelihood Function in very clear and simple terms. Likelihood Function in Machine Learning and Data Science is the joint probability distribution(jpd) of the dataset given …
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Bayesian Inference is simply a way of making statistical inference by applying Bayes’ Theorem. Assuming there is a particular hypothesis H. Let the probability of this hypothesis be p(H). According …
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You already know of Simple Linear Regression. You also know of Logistic Regression. Now we would discuss Multiple Linear Regression. This is a case where we have more than one …
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By now, you probably understand probability as well as probability theory. You also know about the Sum Rule and Product Rule. Then you also understand Bayes’ theorem from Lesson 9 …
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In the previous lesson (Lesson 9), we derived Bayes theorem. So let’s write it out: Also recall that Bayes’ theorem helps us find conditional probabilities given marginal probability. Lets’ now …
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As you already know, one of the four basic theories of Machine Learning is the Probability Theory. Or simply, Probability. And this is one challenge of Machine Learning. Big words …
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Remember that in the previous lecture (Lecture 6), we discuss polynomial curve fitting. We kind of saw that the relationship in a dataset can be represented using a polynomial of …
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