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Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and speed in building scientific algorithms while making the process extremely simple. It comes with a large ecosystem of community-driven packages in machine learning, computer vision, signal processing, parallel processing, image, video, audio, and networking, among others, and builds on top of the Lua community. At the heart of Torch are popular neural network and optimization libraries, which are simple to use while offering maximum flexibility in implementing complex neural network topologies. You can build arbitrary graphs of neural networks and parallelize them over CPUs and GPUs efficiently. Torch is open-source, so you can also start with the code on the GitHub repository. It is constantly evolving and is already used within Facebook, Google, Twitter, NYU, Idiap, Purdue, and several other companies and research labs. The Torch website provides documentation, tutorials, a community wiki, a blog, and support resources. It is a reputable and widely used platform in the field of scientific computing and machine learning."

• Wide support for machine learning algorithms, Puts GPUs first, Easy to use and efficient, Relies on LuaJIT scripting language, Underlying C/CUDA implementation, Maximum flexibility and speed in building scientific algorithms, Large ecosystem of community-driven packages, Popular in machine learning, computer vision, signal processing, parallel processing, image, video, audio, and networking, Builds on top of the Lua community, Popular neural network and optimization libraries, Simple to use, Maximum flexibility in implementing complex neural network topologies, Ability to build arbitrary graphs of neural networks, Efficient parallelization over CPUs and GPUs, Open-source with code available on GitHub, Constantly evolving and used within major companies and research labs, Provides documentation, tutorials, a community wiki, a blog, and support resources, Reputable and widely used platform in scientific computing and machine learning