Machine translation (MT), is the process of translating text from one source language into another target language, is one of the most important applications of NLP. MT is a sequence-to-sequence task. There are a lot of them in NLP. We have a sequence of words in one language as an input, and we want to…
Why NLP is difficult? Text classification is complex, much more complex than image classification for example. The reason, is that nearly all what you need to classify an image is in the image itself. there is no need for an external supposed knowledge. While in text this is not the case. Generally language always refers…
In a previous article I introduced Convolutional Neural Networks (CNN) in an intuitive way. In this article I will present few of the modern architectures of the CNN. Convolutional networks have been showing exceptional results in image classification more than a decade ago. Here we will review some of standard CNN architectures and the context…
Introduction Convolutional neural networks (also called CNNs or ConvNets) are neural networks used traditionally to classify images, for example to identify faces, objects, street signs, tumors,… They have the ability to recognise any kind of data if they get trained with a suitable dataset. CNNs are not limited to image recognition, they have been applied…
