Artificial Neural Networks For Blockchain: A Primer

Artificial neural networks (ANNs) have proven to be extremely useful for solving problems such as classification, regression, function estimation and dimensionality reduction. However, it turns out that different neural network architectures are able to achieve higher performances for certain problems. This article will provide an overview of the most common neural network architectures -- including recurrent neural networks and convolutional neural -- and how they can be implemented to aid blockchain technology. Convolutional neural networks (CNNs) are a type of neural network that is designed to capture increasingly more complex features within its input data. To do this, CNNs are constructed from a sequence of layers, each of which consists of a series of cube-shaped filters.