Machine Learning Articles

Ellen Glover

Updated on March 26, 2025

Supervised learning teaches AI models to predict outcomes using labeled data, while unsupervised learning explores unlabeled data to discover hidden patterns and insights. Take a closer look at the differences between supervised and unsupervised learning.

Paul Barba

Updated on March 25, 2025

Data often reflects the biases that pervade the larger world. To make machine learning processes more equitable, we need to employ a variety of methods to eliminate bias.

Jeff Catlin

Updated on March 25, 2025

Domain-specific AI isn’t here quite yet, but deep language learning models like BERT and GPT-3 suggest it’s just a matter of time before your niche sees its own transformative AI innovations.

Mrinal Tyagi

Updated on March 24, 2025

Image segmentation separates an image into groups of pixels based on variables like proximity to one another, color and brightness for faster processing. Here’s a deep dive into different image segmentation techniques and how each works.

Afroz Chakure

Updated on March 20, 2025

A classification tree is a type of decision tree used to predict categorical or qualitative outcomes from a set of data observations.

Przemek Chojecki

Updated on March 20, 2025

Acquiring data is easy nowadays. To make it useful, though, you need to develop a coherent plan for data usage.

Przemek Chojecki

Updated on March 20, 2025

Although the GPT-3 machine learning model isn’t revolutionary from an algorithmic perspective, it will still usher in a new era of human-machine interactions.

Miranda Hartley

Updated on March 19, 2025

Long-thinking AI emphasizes a more logical, detailed and analytical approach to solving a problem offering lower hallucinations and more accurate outputs. Learn more.

Rushikesh Pupale

Updated on March 19, 2025

A support vector machine is a supervised machine learning algorithm used for classification and regression tasks. Learn how it works and how to implement it in Python.

Anmol Tomar

Updated on March 14, 2025

The elbow method is a technique used to find the optimal number of clusters (K) in k-means clustering, by identifying the “elbow” point on a graph of k-values and their corresponding within-cluster sum of squares (WCSS) values.