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These include software libraries, frameworks, platforms, and tools used for machine learning, deep learning, natural language processing, computer vision, reinforcement learning, artificial general intelligence, and more. Torch development moved in 2017 to pytorch, a port of the library to python Tensorflow is a software library for machine learning and artificial intelligence
It can be used across a range of tasks, but is used mainly for training and inference of neural networks It was created by the idiap research institute at epfl [3][4] it is one of the most popular deep learning frameworks, alongside others such as pytorch
It was developed by the google.
It is developed by google with contributions from nvidia and other community contributors [1][2][3] it is described as bringing together a modified version of autograd (automatic obtaining of the gradient function. Comparison of deep learning software the following tables compare notable software frameworks, libraries, and computer programs for deep learning applications. Keras was first independent software, then integrated into the tensorflow library, and later added support for more
[1] it has a simple, flexible and easily readable syntax [2] its popularity results in a vast ecosystem of libraries, including for deep learning, such as pytorch, tensorflow, keras, google jax The library numpy can be used for manipulating arrays, scipy for scientific and mathematical. [3] it provides luajit interfaces to deep learning algorithms implemented in c
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