Word-to-vector representations

Almost all machine learning and deep learning algorithms manipulate vectors and matrices. The reason they work is because of their base mathematics, which is heavily rooted in linear algebra. So, in short, for both supervised and unsupervised learning, you will need to create matrices of numbers. In other domains, this is not an issue as information is generally captured as numbers. For example, in retail, the sales information for how many units were sold or how much revenue the store is making in the current month is all numbers. Even in a more abstract field such as computer vision, the image is always stored as pixel intensity of the three basic colors: red, green, and blue. 0 for a particular color means no intensity and 255 means the highest possible intensity for the screen. Similarly, in the case of sound, it is stored as power spectral density...