Graph neural networks (GNN) are a type of machine learning algorithm that can extract important information from graphs and make useful predictions.
Deep reinforcement learning is one of the most interesting branches of AI, responsible for achievements such as mastering complex games, self-driving cars, and robotics.
Federated learning is a technique that helps train machine learning models without sending sensitive user data to the cloud.
Learn how deep neural networks detect objects in images in this primer on object detection with deep learning.
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.