Machine Learning Articles

Perez Ogayo

Updated on March 04, 2025

A CUDA Error: Device-Side Assert Triggered can either be caused by an inconsistency between the number of labels and output units in a model or an incorrect input for a loss function. Follow this guide to fix it. 

Edmond Yip

Updated on March 04, 2025

A variational autoencoder (VAE) is a generative AI model that is used to improve the quality of images generated by tools like Stable Diffusion. Here are some applications of VAEs, how to use a VAE in Stable Diffusion and the pros and cons of VAEs.

Mike Thomas

Updated on March 04, 2025

These companies are fine-tuning their marketing efforts with machine learning.

Jye Sawtell-Rickson

Updated on March 03, 2025

Computer vision is a field of artificial intelligence that trains computers to see, interpret and understand the world around them through machine learning techniques. Here’s how it works, why it matters, how it’s used and some challenges to keep in mind.

Jenny Lyons-Cunha

Updated on February 27, 2025

Federated learning is a technique for training an AI model across a network of devices without having to share data with a central server. Here’s a closer look at how it works, its types, applications, challenges and benefits.

Shesh Narayan Gupta

Updated on February 26, 2025

Root mean square propagation (RMSProp) is an adaptive learning rate optimization algorithm designed to improve training and convergence speed in deep learning models.

Giorgos Myrianthous

Updated on February 26, 2025

Light gradient-boosting machine (LightGBM) is an open-source machine learning framework that specializes in handling large data sets and high-dimensional data. Learn more. 

Giorgos Myrianthous

Updated on February 26, 2025

Understanding hyperparameter tuning is crucial to getting the results you want from your machine learning model.

Yukai Tu

Updated on February 21, 2025

AI agents are poised to be the next big thing in tech. First, though, we need to make sure the ecosystem is ready for them.

Ellen Glover

Updated on February 19, 2025

Distillation condenses large AI models into smaller, more efficient ones — cutting down costs and complexity while preserving all the advanced capabilities.