## Machine Learning 101 – Multiple Linear Regression

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 …

## Machine Learning 101 – Minimizing Misclassification Rate in Bayes’ Classifier

In Lecture 4, we learnt about the Bayes’ classifier. Here  we would see how to minimize misclassfication rate in Bayes classifier. Again, we would review …

## 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 …

## Machine Learning 101 – The Bayes’ Classfier

This is the second lecture on classification. It follow the first one: Introduction to Classification. Bayes’ Classifier is a classifier that works based on Bayes’ …

## Machine Learning 101 – Introduction to Classification

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, …

## Machine Learning 101 – Bias-Variance Trade-off

This Lecture follows from Lecture 7 on Underfitting and Overfitting. Here we would discuss Bias-Variance Trade-off. I will try to make this lesson very clear. …

## Machine Learning 101 – Rules of Probability & Bayes’ Theorem

We will now consider some of the important rules of probability. Meanwhile we would also understand the meaning of terms along the line. They include: …

## Machine Learning 101 – Introduction to Probability Theory

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 …

## Machine Learning 101 – Overfitting and Underfitting

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 …

## Machine Learning 101 – Polynomial Curve Fitting

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 …