Machine Learning (ML) is a branch of Artificial Intelligence that enables computers to identify patterns and make predictions from data without being explicitly programmed. ML systems "learn" by analyzing training sets of data and then storing the input/output relationships in memory for future use. The more data that can be supplied to a machine learning system, the better it will become at predicting output from given input. The two most common types of ML are pattern recognition and predictive analytics, which attempt to identify patterns in existing data or predict future trends based on historical trends, respectively. Machine Learning has been used extensively in several industries including finance, healthcare, government, and smart cities as well as within various forms of consumer technology such as household appliances and home assistants.
Machine learning often requires large amounts of labeled data to train the algorithm; therefore, many topics related to machine learning also deal with data science concepts such as scraping, data curation, and visualization.