Knowledge Base

Generative adversarial networks (GANs) are algorithmic architectures that use two neural networks, pitting one against the other (thus the “adversarial”) in order to generate new, synthetic instances of data that can pass for real data.

Convolutional Neural Networks are extremely efficient to solve several categories of problem such as classification, estimation, approximation, recognition, etc.

Machine learning is a subset of artificial intelligence and deep learning is a subset of machine learning. The main difference is that machine learning needs structured (labeled) data and deep learning relies on layer of artificial neural network.