The TensorFlow.js Node.js environment supports using an installed build of Python/C TensorFlow as a back end, which may in turn use the machine’s available hardware acceleration, for example CUDA.

Both PyTorch and TensorFlow offer tutorials on how to use transfer learning for training convolutional neural networks. The TensorFlow transfer learning tutorial demonstrates using transfer ...

That is why Meta started developing PyTorch as a means to offer pretty much the same functionalities as TensorFlow, but making it easier to use. The people behind TensorFlow soon took note of this ...

Keras or TensorFlow? This breakdown shows their differences, use cases, and when to choose each. #KerasVsTensorFlow #MachineLearningTools #AI ...

Besides putting a Raspberry Pi to work on a mini Mars rover, it's now going to be a lot easier to use Google's TensorFlow artificial-intelligence framework with the low-powered computer ...

When the time comes to add an object recognizer to your hack, all you need do is choose from many of the available ones and retrain it for your particular objects of interest. To help with that, [E… ...

According to its site, TensorFlow is an open source software library for numerical computation using data flow graphs. For a layman, TensorFlow can be considered as a system that takes ...

Google acknowledges "military use of machine learning naturally raises valid concerns" but says this project "is for non-offensive uses only." Pentagon using Google's TensorFlow APIs to analyze ...

This article will discuss the seven popular tools and frameworks used for developing AI applications: TensorFlow, PyTorch, Keras, Caffe, Microsoft Cognitive Toolkit, Theano and Apache MXNet.

Using AI for motion-tracking isn’t exactly new; Microsoft’s Kinect was an early example of a consumer product that utilized machine learning. However, it required several sensors and cost $150 ...