K-Nearest Neighbors Algorithm for ML

The k-nearest neighbors (kNN) algorithm is a simple tool that can be used for a large number of real-world problems. In this article, we cover what kNN is, how it works, and how to implement it in machine learning projects.

What Is Anomaly Detection in Machine Learning?

In this article, you will read about different types of outliers and machine learning techniques that help to find anomalies. Learn how you can apply ML anomaly detection techniques to fraud prevention, medical diagnosis, and more.

Is Self-Supervised Learning the Future of AI?

Self-supervised learning is one of the most popular approaches to ML today. SSL algorithms don’t require manual target labeling and can obtain all the information they need from the data. Find out more about how they work in our new post.

Introduction to Polynomial Regression Analysis

What is polynomial regression? When should you use it? In this article, we’ll give you all the answers.

Naive Bayes Algorithm for Beginners

Naive Bayes classifiers are a set of classification algorithms for binary (two-class) and multiclass problem classification. Let’s find out where the Naive Bayes algorithm has proven to be effective and where it hasn't.

An Overview of Machine Learning Optimization Techniques

Find out why ML optimization is necessary and how ML optimization techniques work through simple, practical examples.

A Guide to Deep Learning and Neural Networks

The difference between deep learning and neural networks is often confusing for beginners. What does it mean for an algorithm to be “deep”? What types of neural networks exist out there? You’ll learn all that and more in our guide.

Regression Analysis Overview: The Hows and The Whys

Regression analysis is widely used for making predictions. In this article, you’ll learn what regression models are, what they can and cannot do, and how regression analysis can help with forecasting.

Classification Algorithms: A Tomato-Inspired Overview

Today, we will see how popular classification algorithms can help us, for example, to pick out and sort wonderful, juicy tomatoes.

How to Choose a Machine Learning Technique

Need to build an ML model but don’t know where to start? In this post, we will help you pick the correct machine learning algorithms for your particular use case.

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