Decision Trees (Part 1)

Decision trees are a powerful and versatile machine learning model, which is based on simple decision rules that are…

Pipelines in Scikit-Learn

This article covers a very useful feature provided by the Scikit-Learn library, which can help streamline your machine learning models and make it easier to maintain and deploy them.

K-Nearest Neighbors (KNN): A Comprehensive Guide

Master-Level Questions in Data Science

Most of the data science interview preparation questions you can find online are introductory-level questions and do not necessarily resemble the questions you will get in a real job interview.

K-Means Clustering

In-depth explanation of the popular k-means algorithm including implementation in…

AdaBoost Illustrated

AdaBoost (short for Adaptive Boosting) is a powerful boosting algorithm that can boost the performance of any machine…

Regularization in Machine Learning

Regularization is a widespread technique in machine learning, which is used to control the complexity of the machine learning model and thereby improve its generalization ability.

A Gentle Introduction to Matrix Calculus

Including Applications in Machine Learning

Generative vs. Discriminative Models

We have all heard about generative models lately. Their capabilities for generating text, images, audio and video have shown truly stunning results during the last year. But what generative models really are and how do they differ from other types of machine…