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Navy Marine Corps Intranet. The Navy/Marine Corps Intranet ( NMCI) is a United States Department of the Navy program which was designed to provide the vast majority of information technology services for the entire Department, including the United States Navy and Marine Corps .
ML.NET is a free software machine learning library for the C# and F# programming languages. It also supports Python models when used together with NimbusML. The preview release of ML.NET included transforms for feature engineering like n-gram creation, and learners to handle binary classification, multi-class classification, and regression tasks.
Neural machine translation. Neural machine translation ( NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model. It is the dominant approach today [1] : 293 [2] : 1 and can produce translations that rival ...
A transformer is a deep learning architecture developed by Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention Is All You Need". [1] Text is converted to numerical representations called tokens, and each token is converted into a vector via looking up from a word embedding table. [1]
palletsprojects .com /p /flask /. Flask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries. [2] It has no database abstraction layer, form validation, or any other components where pre-existing third-party libraries provide common functions.
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]
e. In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once.
v. t. e. Multimodal learning, in the context of machine learning, is a type of deep learning using a combination of various modalities of data, such as text, audio, or images, in order to create a more robust model of the real-world phenomena in question. In contrast, singular modal learning would analyze text (typically represented as feature ...