Abstract: Since their introduction over a year ago, Google's TensorFlow package for learning with multilayer neural networks and their Word2Vec representation of words have both gained a high degree ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Abstract: Quantum convolutional neural networks (QCNNs) are a highly appealing architecture that combines quantum computing and deep learning. Inspired by classical convolutional neural network (CNN) ...

If you have trouble following the instruction below, feel free to join OSCER weekly zoom help sessions. If you're doing deep learning neural network research, tensorflow need no introduction. It is ...

TensorFlow.js lets you run machine learning models right in the browser using JavaScript. This quick-start guide shows how to load a model, run predictions, and even train simple neural networks with ...

DGFraud-TF2 is a Graph Neural Network (GNN) based toolbox for fraud detection. It is the Tensorflow 2.X version of DGFraud, which is implemented using TF 1.X. It integrates the implementation & ...

Your browser does not support the audio element. Deprecated: For Keras objects, it's recommended to use the new high-level .keras format and tf.keras.Model.export, as ...

Why floating point is important for developing machine-learning models. What floating-point formats are used with machine learning? Over the last two decades, compute-intensive artificial-intelligence ...