ONLINE GRAPH BUILDER TENSORFLOW DRIVER

TensorFlow was released under the Apache 2.0 license in 2015, and since then it has found widespread use in research, industry, and educational communities. TensorFlow is typically used as an extension of Python, but all those low-level components that allow TF to run on hardware accelerators like GPUs and Google’s Tensor Processing Units are written in compiled languages like C++ and CUDA.

ONLINE GRAPH BUILDER TENSORFLOW DRIVER

The primary utility and development driver for TensorFlow is machine learning, especially deep neural networks, with millions of parameters.

What is TensorFlow?Īt its core, TensorFlow is a software package for the mathematical manipulation, storage, and transfer of tensors, a generalization of the concept of matrices. You’ll also find that, despite the major changes starting with TensorFlow 2.0, the project developers have taken many steps to ensure that backward compatibility can be maintained. TensorFlow still has about 3 times the user base of PyTorch (judging from the repositories on GitHub referencing each framework), and that means more extensions, more tutorials, and more developers collaboratively exploring the space of all possible code errors on Stack Overflow. With eager execution by default, you no longer have to pre-define a static graph, initialize sessions, or worry about tensors falling outside of the proper scope when you get over-zealous in your object-oriented principles. In fact, many of the changes in 2.0 specifically address the alleged shortcomings of TensorFlow. Considering learning a new Python framework for deep learning? If you already know some TensorFlow and are looking for something with a little more dynamism, you no longer have to switch all the way to PyTorch, thanks to some substantial changes coming as part of TensorFlow 2.0.

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