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For example, TensorFlow Recommenders and TensorFlow Graphics are libraries for their respective functionalities in recommendation systems and graphics, TensorFlow Federated provides a framework for decentralized data, and TensorFlow Cloud allows users to directly interact with Google Cloud to integrate their local code to Google Cloud. [68]
Libraries such as TensorFlow C++, Caffe or Shogun can be used. [1] 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. [6] Julia is a language launched in 2012, which intends to combine ease of use and performance.
Download QR code; Print/export Download as PDF; ... Software license [a] Open source Platform ... Tensorflow or PlaidML as backends Yes No Yes Yes [20]
OpenNN, a comprehensive C++ library implementing neural networks. [83] PyTorch, an open-source Tensor and Dynamic neural network in Python. [84] TensorFlow, an open-source software library for machine learning. [85] Theano, a Python library and optimizing compiler for manipulating and evaluating mathematical expressions, especially matrix ...
JAX is a machine learning framework for transforming numerical functions developed by Google with some contributions from Nvidia. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).
OpenNN (Open Neural Networks Library) is a software library written in the C++ programming language which implements neural networks, a main area of deep learning research. [1] The library is open-source , licensed under the GNU Lesser General Public License .
The source code is licensed under Apache License and available on GitHub. [6] InfoWorld magazine awarded the library "The best machine learning tools" in 2017. [11] along with TensorFlow, Pytorch, XGBoost and 8 other libraries. Kaggle listed CatBoost as one of the most frequently used machine learning (ML) frameworks in the world.
Keras was first independent software, then integrated into the TensorFlow library, and later supporting more. "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers, models, or metrics that can be used in native workflows in JAX, TensorFlow, or PyTorch — with ...