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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. [33] [43] 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. [44]
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In machine learning, the term tensor informally refers to two different concepts (i) a way of organizing data and (ii) a multilinear (tensor) transformation. Data may be organized in a multidimensional array (M-way array), informally referred to as a "data tensor"; however, in the strict mathematical sense, a tensor is a multilinear mapping over a set of domain vector spaces to a range vector ...
Matroid released a book with co-author Bharath Ramsundar, TensorFlow for Deep Learning. [26] It introduces the fundamentals of machine learning through TensorFlow and explains how to use TensorFlow to build systems capable of detecting objects in images, understanding human text, and predicting the properties of potential medicines.
NNI (Neural Network Intelligence) is a free and open-source AutoML toolkit developed by Microsoft. [ 3 ] [ 4 ] It is used to automate feature engineering , model compression , neural architecture search , and hyper-parameter tuning .
Libraries for AI include TensorFlow.js, Synaptic and Brain.js. [6] 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. [6] C# can be used to develop high level machine learning models using Microsoft’s .NET suite. ML ...
Up until version 2.3, Keras supported multiple backends, including TensorFlow, Microsoft Cognitive Toolkit, Theano, and PlaidML. [7] [8] [9] As of version 2.4, only TensorFlow was supported. Starting with version 3.0 (as well as its preview version, Keras Core), however, Keras has become multi-backend again, supporting TensorFlow, JAX, and ...
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]