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April 1, 2017

DeepLearningKit

DeepLearningKit is an Open Source with Apache 2.0 License. It is a Deep Learning Framework for Apple’s iOS, OS X and tvOS that is available at github.com/DeepLearningKit/DeepLearningKit. The goal is to support using pre-trained Deep Learning models on all Apple’s devices that have GPU(s). It is developed in Swift to easily run on all platforms such as iOS, OS X and tvOS and Metal to efficiently use on-device GPU to ensure low-latency Deep Learning calculations.DeepLearningKit currently supports using (Deep) Convolutional Neural Networks, such as for image recognition, trained with the Caffe Deep Learning Framework but the long term goal is to support [...]

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April 1, 2017

Torch

Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It offers an easy to use and efficient program to its users, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. Users of Torch will be able to take advantage of its core features such as a powerful N-dimensional array, lots of routines for indexing, slicing, transposing, amazing interface to C, via LuaJIT, linear algebra routines, neural network, and energy-based models, numeric optimization routines, fast and efficient GPU support and embeddable, with ports to iOS, Android and FPGA back ends.The [...]

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April 1, 2017

MLPNeuralNet

MLPNeuralNet is a fast multilayer perceptron neural network library for iOS and Mac OS X. MLPNeuralNet predicts new examples through trained neural networks. It is built on top of Apple’s Accelerate Framework using vectored operations and hardware acceleration (if available). MLPNeuralNet is for users who have engineered a prediction model using Matlab (Python or R) and would like to use it in an iOS application. In that case, MLPNeuralNet is exactly what is needed. MLPNeuralNet is designed to load and run models in forward propagation mode only. Some of the features that users will be able to take advantage of MLPNeuralNet would be Classification, [...]

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