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In this video on pytorch vs tensorflow you will understand about the top deep learning frameworks used in the IT industry, and which one should you use for better performance. So in this pytorch vs tensorflow comparison some important parameters have been taken into consideration to tell you the difference between pytorch and tensorflow also which one is preferred over the other in certain aspects in detail.
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📝Following topics are covered in this video:
00:00 – Pytorch vs Tensorflow
00:06 – What is Pytorch
00:44 – What is Tensorflow
01:42 – Difference between Pytorch and Tensorflow
13:46 – Compare Pytorch vs Tensorflow ; which is better?
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Why Pytorch is important
PyTorch is a pretty intuitive tensor library which can be used for creating neural networks. PyTorch is different from other deep learning frameworks in that it uses dynamic computation graphs. While static computational graphs (like those used in TensorFlow) are defined prior to runtime, dynamic graphs are defined “on the fly” via the forward computation.
Why Tensorflow is important
TensorFlow is an open source machine learning framework for carrying out high-performance numerical computations. It provides excellent architecture support which allows easy deployment of computations across a variety of platforms ranging from desktops to clusters of servers, mobiles, and edge devices.
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