Dimensionality reduction slashes the costs of machine learning and sometimes makes it possible to solve complicated problems with simpler models.
Membership inference attacks can detect examples used to train machine learning models even after those examples have been discarded.
Semi-supervised learning helps you solve classification problems when you don't have labeled data to train your machine learning model.
Ensemble learning is a popular machine learning technique that combines several models to improve overall accuracy of AI algorithms.
Data poisoning attack target the training of machine learning algorithms and cause them to behave maliciously during inference.
Deepfakes use deep learning algorithm to swap parts of image. They have given rise to a new generation of AI-doctored videos.
By Vanessa Kearney
Any business looking to streamline its processes and move to more efficient models will encounter automation, machine learning, and artificial intelligence along the way. Although in 2020 we’re a far cry from sentient...
One-shot learning allows deep learning algorithms to measure the similarity and difference between two images.
Adversarial examples are slight manipulations that cause machine learning algorithms to misclassify images while going unnoticed to the human eye.
Recurrent neural networks enable computers to process text, videos, time series, and other sequential data.