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 …
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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 …
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: …
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 …
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 …
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, …
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’ …
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 …
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 …
Welcome back! So we’ll continue with Questions 31 to 40 of our Machine Learning Q&A. You can find Question 1 to 20 below Questions 1 …
We would build a Microservices in Java Step by step. Find the Source Codes here This microservice is based on a simple hypothetical Hospital Information …