Machine Learning 101 – K-Nearest Neighbors Classifier
In the last lecture, we discussed Bayes’ Classifier. Now, we are going to discuss K-Nearest Neighbors Classifier. Remember that Bayes Classifier tries to classify X …
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In the last lecture, we discussed Bayes’ Classifier. Now, we are going to discuss K-Nearest Neighbors Classifier. Remember that Bayes Classifier tries to classify X …
In subsequent lectures, we have discussed regression problems. Now we would apply the same analysis to classification but with little adjustment. In case of classification, …
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 …
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 …
This is Lecture 6 of Machine Learning 101. We would discuss Polynomial Curve Fitting. Now don’t bother if the name makes it appear tough. This …
Let’s go back to the regression problem we solved in Lecture 4. We are given a dataset. You need to find the relationship between the …
This is Lecture 4 of the Machine Learning 101. It follows from Lecture 3. In this lecture, we would solve some regression problems. So brace …
This is lesson 3 of Machine Learning 101. We are going to examine classes of machine learning problems. In Lecture 2 we already mentioned a …
The is lesson 2 of our Machine Learning 101 course. This follows from Lesson 1. We would cover the following: The Goal of Machine Learning …
This is the very first of a complete Machine Learning course . So if you intend to learn Machine Learning, then you are in the right place. …