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Keras is an open-source library that provides a Python interface for artificial neural networks. 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 ...
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [1] [2] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain. Artificial ...
NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm (GA) for the generation of evolving artificial neural networks (a neuroevolution technique) developed by Kenneth Stanley and Risto Miikkulainen in 2002 while at The University of Texas at Austin. It alters both the weighting parameters and structures of networks, attempting ...
The nn package is used for building neural networks. It is divided into modular objects that share a common Module interface. Modules have a forward() and backward() method that allow them to feedforward and backpropagate, respectively. Modules can be joined using module composites, like Sequential, Parallel and Concat to create complex task ...
: neural network parameters. In words, it is a neural network that maps an input into an output , with the hidden vector playing the role of "memory", a partial record of all previous input-output pairs. At each step, it transforms input to an output, and modifies its "memory" to help it to better perform future processing.
FAN supports cross-platform execution of single and multilayer networks. It also supports fixed-point and floating-point arithmetic. It includes functions that simplify the creating, training and testing of neural networks. It has bindings for over 20 programming languages, including commonly used languages such as PHP, C# and Python.
Users specify neuron models by giving their differential equations in standard mathematical form as strings, create groups of neurons and connect them via synapses. This is in contrast to the approach taken by many neural simulators in which users select from a predefined set of neuron models. Brian is written in Python.
Chainer is an open source deep learning framework written purely in Python on top of NumPy and CuPy Python libraries. The development is led by Japanese venture company Preferred Networks in partnership with IBM, Intel, Microsoft, and Nvidia.