In other words, machine learning algorithms enable computers to identify patterns and relationships within a dataset, and use that knowledge to make predictions or decisions about new data. This is done by training the machine learning model on a labeled dataset, where the correct outputs are known, and then using that trained model to make predictions on new, unlabeled data.
There are several types of machine learning, including supervised learning, unsupervised learning, and reinforcement learning. Supervised learning involves training a model on labeled data, while unsupervised learning involves finding patterns in unlabeled data. Reinforcement learning involves training a model through a system of rewards and punishments, in order to optimize its decision-making abilities. Machine learning has numerous applications across a wide range of industries, from healthcare and finance to marketing and entertainment.
