Machine Learning Articles

Abhijeet Pujara

Updated on May 22, 2025

MobileNet is a mobile-first class of convolutional neural network (CNN) that was open-sourced by Google and provides a starting point for training classifiers through a lightweight model.

Sean Benhur

Updated on May 22, 2025

A Siamese neural network (SNN) is a type of neural network architecture that contains two or more identical sub-networks with the same parameters and weights. SNNs can make predictions using only a few images per class.

Bharath Krishnamurthy

Updated on May 22, 2025

Advancements in artificial intelligence and deep learning have led to the rapid development of chess engines. Here’s a look at the history of chess AI, how it continues to evolve and how developers can get started in building their own chess AI engines.

Parul Pandey

Updated on May 22, 2025

A vector norm is a function that measures the size or magnitude of a vector by quantifying its length from the origin. Vector norms are an important concept to machine learning. This guide breaks down the idea behind the L¹, L², L∞ and Lᵖ norms.

John Hession

Updated on May 22, 2025

A Liquid neural network (LNN) is a new neural network architecture that relies on fewer, dynamic nodes to handle time series prediction tasks. Here’s how it works. 

Dhanam Parekh

Updated on May 22, 2025

A sorting algorithm is an algorithm used to rearrange elements in a list or array based on a specified order. Here's a review of common sorting algorithms and their performance analysis, ranked from slowest to fastest.

Satyam Kumar

Updated on May 22, 2025

C-means clustering is a clustering technique that groups data points into different clusters and assigns a probability score, allowing a data point to belong to multiple clusters to varying degrees. Here’s how it works and how to install it on Python.

Sunny Srinidhi

Updated on May 22, 2025

Lemmatization is a text pre-processing technique used in natural language processing (NLP) models to break a word down to its root meaning to identify similarities. It is one of the most common text pre-processing techniques used in NLP.

Kurtis Pykes

Updated on May 22, 2025

Cohen’s kappa is a statistical metric that measures the reliability of two raters who are evaluating the same thing, accounting for the possibility that they could agree by chance. Here’s how it works and how to calculate it.

Akash Desarda

Updated on May 22, 2025

AdaBoost (Adaptive Boosting) is a machine learning boosting technique used as an ensemble method to adjust the weights of training samples and combine multiple weak classifiers into a single strong classifier.