This is a new series looking at practical applications of Machine Learning from a Linux perspective. We only feature free and open source software in this series. Let's clear up one potential source of confusion at the outset. The two terms mean different things. In essence, Machine Learning is the practice of using algorithms to parse data, learn insights from that data, and then make a determination or prediction.

Machine learning is about learning some properties of a data set and then testing those properties against another data set. A common practice in machine learning is to evaluate an algorithm by splitting a data set into two. We call one of those sets the training set, on which we learn some properties; we call the other set the testing set, on which we test the learned properties. Stable Diffusion is a deep learning text-to-image diffusion model capable of generating photo-realistic images given any text input. In seconds you can create stunning artwork. Stable Diffusion uses a kind of diffusion model, called a latent diffusion model.

GFPGAN is deep learning software for real-world face restoration. This software can radically improve the quality of images.

Let's clear up one potential source of confusion at the outset. The two terms mean different things. In essence, Machine Learning is the practice of using algorithms to parse data, learn insights from that data, and then make a determination or prediction.

Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages. It includes word and sentence tokenization, text classification and sentiment analysis, spelling correction, information extraction, parsing, meaning extraction, and question answering. In our formative years, we master the basics of spoken and written language. However, the vast majority of us do not progress past some basic processing rules when we learn how to handle text in our applications. Yet unstructured software comprises the majority of the data we see.