Torch - Scientific Computing Framework with Machine Learning and GPU Support
Torch is a powerful scientific computing framework designed with wide support for machine learning algorithms and prioritizes GPU utilization. It offers efficient scripting and is embedded with ports to iOS and Android backends.
Torch Product Information
What is Torch?
Torch provides a powerful N-dimensional array, extensive routines for indexing and slicing, and an interface to C via LuaJIT. It includes linear algebra routines, neural network and energy-based models, as well as numeric optimization routines. The framework offers fast and efficient GPU support, making it suitable for machine learning, computer vision, signal processing, parallel processing, and various other applications.
How to Use Torch?
Begin by downloading and trying Torch using the provided guide. As an open-source framework, users can also access and explore the code on GitHub. Torch is continuously evolving and is already utilized by prominent companies and research labs such as Facebook, Google, Twitter, NYU, IDIAP, and Purdue.
Core Features of Torch
- Powerful N-dimensional array
- Linear algebra routines
- Neural network and energy-based models
- Numeric optimization routines
- Fast and efficient GPU support
- Embeddable with ports to iOS and Android backends
Use Cases of Torch
- Machine learning
- Computer vision
- Signal processing
- Parallel processing
- Scientific computing
FAQ about Torch
What is Torch?
Torch is a scientific computing framework with wide support for machine learning algorithms, efficient GPU utilization, and an easy-to-use scripting language, LuaJIT.
Why use Torch?
Torch provides maximum flexibility and speed in building scientific algorithms while simplifying the process. It is open-source and already utilized by prominent companies and research labs.
How can I start using Torch?
You can begin using Torch by downloading and trying it with the provided guide. Additionally, as an open-source framework, you can explore the code on GitHub.
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