Examples of using Tensorflow in English and their translations into Hebrew
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Computer
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Programming
Experiment with TensorFlow.
Install TensorFlow with pip.
Experience with TensorFlow.
TensorFlow is Google Brain's second era system.
Google's library, TensorFlow, is particularly popular.
Tensorflow is the brainchild of Google brain team.
Most recently he lead the TensorFlow Fold project.
TensorFlow is Google Brain's second-generation system.
Experience with at least onedeep learning framework such as PyTorch or Tensorflow.
TensorFlow is the second generation system from Google Brain.
Familiar with at least one of the common deep learning framework:Pytorch, Tensorflow.
TensorFlow is an open-source second generation of the Google Brain system.
Hands-on experience with at least one majordeep learning framework e.g. pyTorch, TensorFlow.
TensorFlow is Google Brain's second generation system.
In June 2016,Dean stated that 1,500 repositories on GitHub mentioned TensorFlow, of which only 5 were from Google.
TensorFlow is Google Brain's second-generation system.
In June 2016,Google's Jeff Dean stated that 1,500 repositories on GitHub mentioned TensorFlow, of which only 5 were from Google.
The PVC supports TensorFlow for machine learning(and Halide for image processing).
The course teaches statistics for business analysis, machine learning algorithms,deep learning with TensorFlow, and programming with Python.
TensorFLow is the second-generation machine learning system of Google Brain.
By applying the Cray PE Machine Learning Plugin,the app attains unprecedented scaling of the TensorFlow Deep Learning framework to more than 8,000 nodes.
In May 2016, Google announced its Tensor processing unit(TPU),an ASIC built specifically for machine learning and tailored for TensorFlow.
Our goal was to demonstrate that TensorFlow can run at scale on multiple nodes efficiently," said Deborah Bard, a big data architect at NERSC and a co-author of the technical paper.
The application leverages the Cray PE MachineLearning Plugin to achieve unprecedented scaling of the TensorFlow Deep Learning framework to more than 8,000 nodes.
In May 2016, Google announced its Tensor Processing Unit(TPU), an application-specific integrated circuit(a hardware chip)built specifically for machine learning and tailored for TensorFlow.
If you truly know how to work with machine-learning tools andlibraries such as Google's TensorFlow, make sure to highlight that on your résumé- those are collectively a very big deal right now.
The team also wanted to ensure that TensorFlow ran efficiently and effectively on a single Intel® Xeon Phi™ processor node with 3D volumes, which are common in science but not so much in industry, where most deep learning applications deal with 2D image data sets.
As far as we are aware, this is the largest ever deployment of TensorFlow on CPUs, and we think it is the largest attempt to run TensorFlow on the largest number of CPU nodes.”.