Gorgonia is a library that helps facilitate machine learning in Go. Write and evaluate mathematical equations involving multidimensional arrays easily. If this sounds like Theano or TensorFlow, it's because the idea is quite similar. Specifically, the library is pretty low-level, like Theano, but has higher goals like Tensorflow.
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Gorgonia can perform automatic differentiation, symbolic differentiation, gradient descent optimizations, numerical stabilization, distributed computing. 
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The primary goal for Gorgonia is to be a highly performant machine learning/graph computation-based library that can scale across multiple machines. It should bring the appeal of Go (simple compilation and deployment process) to the ML world. It's a long way from there currently, however, the baby steps are already there.




Gorgonia is a library that helps facilitate machine learning in Go. Write and evaluate mathematical equations involving multidimensional arrays easily. If this sounds like Theano or TensorFlow, it's because the idea is quite similar. Specifically, the library is pretty low-level, like Theano, but has higher goals like Tensorflow.



Gorgonia - Library that helps facilitate machine learning in Go

Theano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy. Its features include tight integration with NumPy, transparent use of a GPU, dynamic C code generation and lot more.

Theano - Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs.

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Gorgonia - Library that helps facilitate machine learning in Go

Theano - Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs.

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Gorgonia - Library that helps facilitate machine learning in Go

Theano - Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs.

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