The transformer model has become one of the main highlights of advances in deep learning and deep neural networks.
Neural architecture search NAS is a series of machine learning techniques that can help discover optimal neural networks for a given problem.
Support vector machine (SVM) is a type of machine learning algorithm that can be used for classification and regression tasks.
Data augmentation improves machine learning performance by generating new training examples from existing data.
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.