The artificial intelligence community has long struggled with a fundamental challenge of making AI systems transparent and ...

Neural Network , Convolutional Neural Network , TensorFlow , Optical Character Recognition , Handwritten Digits , Handwritten Digit Recognition , Networks In Python , Machine Learning , Deep Learning ...

Currently, TensorFlow's performance for convolutional neural networks (CNNs) on GPU can be further optimized. The goal of this issue is to identify and implement improvements that enhance the speed ...

TensorFlow GNN (TF-GNN) is a scalable library for Graph Neural Networks in TensorFlow. This Python library enables GNN training and inference on graph-structured data by utilizing heterogeneous ...

Building and creating Neural Networks is mainly associated with such languages/environments as Python, R, or Matlab. However, there have been some new possibilities in the last few years.

Dr. James McCaffrey of Microsoft Research details the 'Hello World' of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset.

Convolutional neural networks use principles from linear algebra, notably matrix multiplication, to discover patterns inside an image, making them more scalable for image classification and object ...