Deep learning is a subset of machine learning methods based on neural networks with representation learning. The field takes inspiration from biological...

Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the...

A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention mechanism, proposed in a 2017 paper...

In deep learning, fine-tuning is an approach to transfer learning in which the parameters of a pre-trained model are trained on new data. Fine-tuning can...

"Deep Learning" is the fourth episode of the twenty-sixth season of the American animated television series South Park, and the 323rd episode of the series...

A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and...

An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator or computer system designed...

Deep learning super sampling (DLSS) is a family of real-time deep learning image enhancement and upscaling technologies developed by Nvidia that are exclusive...

Mamba is a deep learning architecture focused on sequence modeling. It was developed by researchers from Carnegie Mellon University and Princeton University...

Q-learning algorithm. In 2014, Google DeepMind patented an application of Q-learning to deep learning, titled "deep reinforcement learning" or "deep Q-learning"...

Networks, causing the US government to drastically increase funding into deep learning research. This led to "the Golden Age of AI" fueled by the optimistic...

compares notable software frameworks, libraries and computer programs for deep learning. Licenses here are a summary, and are not taken to be complete statements...

In U.S. education, deeper learning is a set of student educational outcomes including acquisition of robust core academic content, higher-order thinking...

Multimodal learning, in the context of machine learning, is a type of deep learning using multiple modalities of data, such as text, audio, or images....

Topological Deep Learning (TDL). is a research field that extends deep learning to handle complex, non-Euclidean data structures. Traditional deep learning models...

as AI winter. Funding and interest vastly increased after 2012 when deep learning outperformed previous AI techniques. This growth accelerated further...

features by itself via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different...

generalization of various learning algorithms is an active topic of current research, especially for deep learning algorithms. Machine learning and statistics are...

Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Q-learning at its simplest...

Deep learning anti-aliasing (DLAA) is a form of spatial anti-aliasing created by Nvidia. DLAA depends on and requires Tensor Cores available in Nvidia...

basic ingredients of the deep learning systems of today. Group method of data handling, a method to train arbitrarily deep neural networks was published...

Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech)...

artificial intelligence and deep learning; including self-driving cars, healthcare, high-performance computing, and Nvidia Deep Learning Institute (DLI) training...

In machine learning, a deep belief network (DBN) is a generative graphical model, or alternatively a class of deep neural network, composed of multiple...

deep learning software. On August 9, 2016, it was acquired by Intel, for an estimated $408 million. The company's (now discontinued) open-source deep...

often built in with deep learning libraries such as Keras. Time-based learning schedules alter the learning rate depending on the learning rate of the previous...

chess) after a few days of play against itself using reinforcement learning. In 2020, DeepMind made significant advances in the problem of protein folding...

Deepfakes (a portmanteau of 'deep learning' and 'fake') are images, videos, or audio which are edited or generated using artificial intelligence tools...

Things, and pharmaceuticals. Federated learning aims at training a machine learning algorithm, for instance deep neural networks, on multiple local datasets...

Google Brain was a deep learning artificial intelligence research team that served as the sole AI branch of Google before being incorporated under the...