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JavaScript is widely used for web applications and can notably be executed with web browsers. Libraries for AI include TensorFlow.js, Synaptic and Brain.js. Julia is a language launched in 2012, which intends to combine ease of use and performance. It is mostly used for numerical analysis, computational science, and machine learning.
TensorFlow serves as a core platform and library for machine learning. TensorFlow's APIs use Keras to allow users to make their own machine-learning models. [ 41] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving.
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] Recently, artificial neural networks have been able to surpass many previous approaches in ...
Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms. It is also used in situations where it is necessary for the algorithm to dynamically adapt to new patterns in the data, or when the data itself is ...
Many AI platforms use Wikipedia data, [302] mainly for training machine learning applications. There is research and development of various artificial intelligence applications for Wikipedia such as for identifying outdated sentences, [ 303 ] detecting covert vandalism [ 304 ] or recommending articles and tasks to new editors.
t. e. Google DeepMind Technologies Limited is a British-American artificial intelligence research laboratory which serves as a subsidiary of Google. Founded in the UK in 2010, it was acquired by Google in 2014 [6] and merged with Google AI 's Google Brain division to become Google DeepMind in April 2023. The company is based in London, with ...
Deep learning is the subset of machine learning methods based on neural networks with representation learning. The adjective "deep" refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised. [ 2]
t. e. 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. In contrast, unimodal models can process only one type of data, such as text (typically represented as feature vectors) or images. Multimodal learning is different from combining unimodal ...
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