Torch Description
Torch is a scientific computing platform that supports machine learning algorithms and has wide support for them. It is simple to use and efficient thanks to a fast scripting language, LuaJIT and an underlying C/CUDA implementation. Torch's goal is to allow you maximum flexibility and speed when building your scientific algorithms, while keeping it simple. Torch includes a large number of community-driven packages for machine learning, signal processing and parallel processing. It also builds on the Lua community. The core of Torch is the popular optimization and neural network libraries. These libraries are easy to use while allowing for maximum flexibility when implementing complex neural networks topologies. You can create arbitrary graphs of neuro networks and parallelize them over CPUs or GPUs in an efficient way.
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Neural Designer
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Machine Learning can be applied in different industries. These are some examples of machine learning solutions:
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- In healthcare: medical diagnosis, prognosis and activity recognition, microarray analysis and drug design.
Neural Designer's strength is its ability to intuitively build predictive models and perform complex operations.
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PyTorch
TorchScript allows you to seamlessly switch between graph and eager modes. TorchServe accelerates the path to production. The torch-distributed backend allows for distributed training and performance optimization in production and research. PyTorch is supported by a rich ecosystem of libraries and tools that supports NLP, computer vision, and other areas. PyTorch is well-supported on major cloud platforms, allowing for frictionless development and easy scaling. Select your preferences, then run the install command. Stable is the most current supported and tested version of PyTorch. This version should be compatible with many users. Preview is available for those who want the latest, but not fully tested, and supported 1.10 builds that are generated every night. Please ensure you have met the prerequisites, such as numpy, depending on which package manager you use. Anaconda is our preferred package manager, as it installs all dependencies.
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Accord.NET Framework
The Accord.NET Framework combines a.NET machine-learning framework with audio and image processing library completely written in C#. It provides a complete framework to build production-grade computer vision, signal processing, and statistics applications, even for commercial use. The extensive set of sample applications provides a quick start for getting up and running quickly. A detailed documentation and wiki help fill in the details.
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Company Details
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Torch
Website:
torch.ch/
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SaaS
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Documentation
Videos
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