enow.com Web Search

Search results

1. Results from the WOW.Com Content Network

2. Machine learning - Wikipedia

   en.wikipedia.org/wiki/Machine_learning

   Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [ 1 ]

3. Transformer (deep learning architecture) - Wikipedia

   en.wikipedia.org/wiki/Transformer_(deep_learning...

   A standard Transformer architecture, showing on the left an encoder, and on the right a decoder. Note: it uses the pre-LN convention, which is different from the post-LN convention used in the original 2017 Transformer. A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention ...

4. Neural network (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Neural_network_(machine...

   v. t. e. In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [ 1 ][ 2 ] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain.

5. Convolutional neural network - Wikipedia

   en.wikipedia.org/wiki/Convolutional_neural_network

   t. e. A convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns 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 types of data including text, images and audio. [ 1 ]

6. Active learning (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Active_learning_(machine...

   e. Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...

7. Attention (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Attention_(machine_learning)

   Attention is a machine learning method that determines the relative importance of each component in a sequence relative to the other components in that sequence. In natural language processing, importance is represented by "soft" weights assigned to each word in a sentence. More generally, attention encodes vectors called token embeddings ...

8. Outline of machine learning - Wikipedia

   en.wikipedia.org/wiki/Outline_of_machine_learning

   The following outline is provided as an overview of and topical guide to machine learning: Machine learning – a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. [ 1 ] In 1959, Arthur Samuel defined machine learning as a "field of ...

9. Variational autoencoder - Wikipedia

   en.wikipedia.org/wiki/Variational_autoencoder

   The decoder receives as input the information sampled from the latent space and produces as similar as possible to . In machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling. [ 1 ] It is part of the families of probabilistic graphical models and ...