Graphs: One of the reasons for TensorFlow’s popularity is its graph ... to deploy machine learning models on devices with limited computational resources, such as smartphones, tablets, and ...

TensorFlow also received a new graphical debugger that will allow developers to view how the internal nodes of a computational graph are functioning in order to understand better the way their ...

Graph from StackOverflow trends. StackOverflow traffic for TensorFlow might not be declining ... academic institutions don’t have the massive computational power needed to build large models.

"We just call them computational graphs. All machine learning models are best expressed as graphs -- this is how TensorFlow works as well. It's just that our graphs are orders of magnitude more ...

Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process ...

While deep neural networks are all the rage, the complexity of the major frameworks has been a barrier to their use for developers new to machine learning. There have been several proposals for ...