There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. In supervised learning, algorithms are trained using labeled data, where both input and output variables are known, to make predictions or classifications on unseen data. Unsupervised learning, on the other hand, involves training algorithms on unlabeled data, allowing them to discover patterns and relationships without specific guidance. This type of learning is useful for clustering similar data points, dimensionality reduction, and anomaly detection. Lastly, reinforcement learning involves training algorithms to interact with an environment and learn through trial and error, with the aim of maximizing rewards or minimizing penalties. This type of learning is commonly used in robotics, gaming, and optimization problems.
This mind map was published on 7 September 2023 and has been viewed 84 times.