Mobile AI Through Machine Learning Algorithms

Machine learning (ML) is a method of artificial intelligence (AI) in which data is used to train a machine so that it can make decisions or predictions on its own. In a previous blog, Setting up your machine learning projects for success, we discussed how data and modelling play a key role in allowing a machine to learn and improve, and our e-book explains how ML fits into the bigger picture of AI. An ML algorithm is a key element that ties this all together, and as we'll discover in this blog, there are four main categories of ML algorithms – supervised machine learning, unsupervised machine learning, semi-supervised machine learning, and reinforcement machine learning. Many of today's ML algorithms can be considered supervised, which means the model is iteratively trained by running the algorithm and comparing its output against data that is known to be correct. Once training is complete, the algorithm and model are ready for inference.