With Python and NumPy getting lots of exposure lately, I'll show how to use those tools to build a simple feed-forward neural network.

You don't have to resort to writing C++ to work with popular machine learning libraries such as Microsoft's CNTK and Google's TensorFlow. Instead, we'll use some Python and NumPy to tackle the task of ...

TensorFlow has since improved its support for eager execution mode, but PyTorch is still popular in the academic and research communities.

Google today released TensorFlow Graph Neural Networks (TF-GNN) in alpha, a library designed to make it easier to work with graph structured data using TensorFlow, its machine learning framework.

Step-by-step coding a full deep neural network with zero libraries — just logic and Python. #NeuralNetwork #PythonCode #DeepLearning Donald Trump's remarks about Putin leave Russian state TV ...

Hands-on coding of a multiclass neural network from scratch, with softmax and one-hot encoding. #Softmax #MulticlassClassification #PythonAI ...

Pete Warden, Technical Lead of TensorFlow at Google commented: "CEVA has been at the forefront of machine learning and neural networks inferencing for embedded systems and understands that the ...

Google open-sources ‘TensorFlow’ machine learning system, offering its neural network to outside developers by James Risley on November 9, 2015 at 10:15 am ...

Google (the real Google, within Alphabet) has announced a new, open-source machine learning platform called TensorFlow, one which could greatly accelerate the pace at which neural networks are ...