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2. Convolutional neural network - Wikipedia

   en.wikipedia.org/wiki/Convolutional_neural_network

   v. 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 ]

3. Recurrent neural network - Wikipedia

   en.wikipedia.org/wiki/Recurrent_neural_network

   v. t. e. Recurrent neural networks (RNNs) are a class of artificial neural networks for sequential data processing. Unlike feedforward neural networks, which process data in a single pass, RNNs process data across multiple time steps, making them well-adapted for modelling and processing text, speech, and time series. [ 1 ]

4. Transformer (deep learning architecture) - Wikipedia

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

   t. e. 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 ...

5. Artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Artificial_intelligence

   Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

6. Long short-term memory - Wikipedia

   en.wikipedia.org/wiki/Long_short-term_memory

   The Long Short-Term Memory (LSTM) cell can process data sequentially and keep its hidden state through time. Long short-term memory (LSTM) [ 1 ] is a type of recurrent neural network (RNN) aimed at dealing with the vanishing gradient problem [ 2 ] present in traditional RNNs. Its relative insensitivity to gap length is its advantage over other ...

7. Machine learning - Wikipedia

   en.wikipedia.org/wiki/Machine_learning

   t. e. 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 ]

8. Self-organizing map - Wikipedia

   en.wikipedia.org/wiki/Self-organizing_map

   Self-organizing map. A self-organizing map (SOM) or self-organizing feature map (SOFM) is an unsupervised machine learning technique used to produce a low-dimensional (typically two-dimensional) representation of a higher-dimensional data set while preserving the topological structure of the data.

9. BERT (language model) - Wikipedia

   en.wikipedia.org/wiki/BERT_(language_model)

   Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [ 1 ][ 2 ] It learns to represent text as a sequence of vectors using self-supervised learning. It uses the encoder-only transformer architecture. It is notable for its dramatic improvement over previous state ...