This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and source codes with explanation, for both TF v1 & v2. Some examples ...

Your browser does not support the audio element. Today, I’m honoured to be talking to the GANFather, the inventor of Generative Adversarial Networks, a pioneer of ...

Neuromorphic computing, inspired by the human brain, is considered as the next-generation paradigm for artificial intelligence (AI), offering dramatically increased speed and lower energy consumption.

Abstract: Adversarial examples that can fool neural network classifiers have attracted much attention. Existing approaches to detect adversarial examples leverage a supervised scheme in generating ...

Most machine learning models get around the same ~99% test accuracy on MNIST. Our dataset, MNIST-1D, is 100x smaller (default sample size: 4000+1000; dimensionality: 40) and does a better job of ...

Abstract: Deep neural networks yield desirable performance in text, image, and speech classification. However, these networks are vulnerable to adversarial examples. An adversarial example is a sample ...

Dr. James McCaffrey of Microsoft Research demonstrates how to fetch and prepare MNIST data for image recognition machine learning problems. Many machine learning problems fall into one of three ...