Keras 与 PyTorch

Keras和PyTorch是两个最强大的开源机器学习库。

Keras是一个基于Python的开源库，用于深度学习（用于神经网络）。它可以在 TensorFlow、Microsoft CNTK 或 Theano 之上运行。它非常易于理解和使用，适合快速实验。 Keras 模型既可以在 CPU 上运行，也可以在 GPU 上运行。

PyTorch是由 Facebook 的 AI 研究小组开发的开源机器学习库。它可以与Python和 C++ 集成。它因其高效的内存使用和轻松调试神经网络的能力而广受欢迎。

让我们看看 Keras 和 PyTorch 之间的区别。

S.No	Keras	PyTorch
1.	Keras was released in March 2015.	While PyTorch was released in October 2016.
2.	Keras has a high level API.	While PyTorch has a low level API.
3.	Keras is comparatively slower in speed.	While PyTorch has a higher speed than Keras, suitable for high performance.
4.	Keras has a simple architecture,making it more readable and easy to use.	While PyTorch has very low readablility due to a complex architecture.
5.	Keras has a smaller community support.	While PyTorch has a stronger community support.
6.	Keras is mostly used for small datasets due to its slow speed.	While PyTorch is preferred for large datasets and high performance.
7.	Debugging in Keras is difficult due to presence of computational junk.	While debugging in PyTorch is easier and faster.
8.	Keras provides static computation graphs.	While PyTorch provides dynamic computation graphs.
9.	Backend for Keras include:TensorFlow, Theano and Microsoft CNTK backend.	While PyTorch has no backend implementation.