In this tutorial, we will learn our next machine-learning model called Naive Bayes. Naive Bayes is widely recognized as a sophisticated and effective tool known for its simplicity. Rooted in ...

In this tutorial, we are going to learn an advanced concept related to decision trees called random forests. The idea behind random forests is the concept of ensembling. Sir Francis ...

In this post, we will learn about our next machine-learning algorithm, Decision Trees. Imagine you're trying to decide what movie to watch. You ask simple questions like "Do you want ...

In this post, we will learn about our next machine learning algorithm called support vector machine or SVM or support vector networks. This is a crucial concept and a powerful ...

In the previous post, we learned about PCA and how to use PCA in machine learning for various applications. In this tutorial, we are going to learn about linear discriminant ...

In the previous post, we learned about SVD and how to use SVD for low-rank approximation. Building upon the concepts of SVD now let's learn about principal component analysis and ...

The singular value decomposition (SVD) is a crucial concept for machine learning that builds the foundation of many algorithms you will use throughout your machine learning journey. It's not only ...

AI these days seems to be a hot topic, maybe because of the release of ChatGPT or maybe I feel that way because of the way we consume information on ...