Artificial Intelligence (AI) is on a trajectory to become ubiquitous in every area of our lives. In this post, we explore three current applications of artificial intelligence in the real world and the machine learning techniques that make them work.
Document classification is currently one of the most important branches of Natural Language Processing (NLP). The general idea is to automatically classify documents into categories using machine learning algorithms.
The applications are almost endless, we can classify: patient records, movie reviews, webpages, emails (spam vs not spam), and in fact anything text based.
The goal for this project was to determine from raw neural activity what the volunteer was thinking at any given time. This form of analysis have many direct applications, for example: prosthesis moving, computer games which interface with brain activity, and even piloting vehicles without need for physical interactions.
Natural language processing has been used in speech recognition, spell-checking, document classification, and more. Moreover, it's a stepping stone to developing strong AI, one which can intelligently parse information given to it better than a human.
Recommender systems are reshaping the business world, especially E-commerce, in an unprecedented manner. They learn patterns of behaviors to predict someone's preference on a set of items they have not experienced. Over the past few years, thousands of companies have used recommender systems to help their customers find products to purchase, new movies to watch, songs to listen to, and even people they should interact with.
Walmart recently hosted a Kaggle competition with the aim of improving a customers' shopping experience by segmenting their store visits into different trip types. Whether they're on a last minute run for school supplies or picking up their monthly prescriptions, classifying trip types enables Walmart to create the best shopping experience for every customer.