I had great fun writing neural network software in the 90s, and I have been anxious to try creating some using TensorFlow. Google’s machine intelligence framework is the new hotness right now… ...

Mapping data flows are authored using a design surface know as the data flow graph. In the graph, transformation logic is built left-to-right and additional data streams are added top-down. To add a ...

Creating Data Flow Graphs from java input classes. With JavaDataFlow you can create data flow graphs. This is a directed graph where a node represents data (e.g. fields, inputParameters, etc.) and the ...

Deep graph convolutional networks (GCNs) have shown promising performance in traffic prediction tasks, but their practical deployment on resource-constrained devices faces challenges. First, few ...

Modern data analytics applications are increasingly characterized by exceedingly large and multidimensional data sources. This represents a challenge for traditional machine learning models, as the ...

tensor = tf.cast(audio_tensor, tf.float32) / 32768.0 plt.figure() plt.plot(tensor.numpy()) Output: Here we can see that in the graph, with respect to the loudness, the frequency of the graph is ...

TensorFlow has released TensorFlow Graph Neural Networks (TF-GNNs), a library designed to make it easy to work with graph-structured data.TF-GNN is a set of TensorFlow building components for ...