• Unsupervised Learning: Unsupervised learning algorithms are used to discover patterns or structures in unlabeled data Common unsupervised learning techniques include clustering, dimensionality reduction, and association rule learning
The field of AI has continued to grow quickly, with advantages in deep learning and other machine learning techniques leading to significant breakthroughs in areas such as image recognition, speech recognition, and natural language processing AI systems are now capable of performing complex tasks that were once thought to be the exclusive domain of humans
• Supervised Learning: Supervised learning algorithms are trained using labeled examples, such as input output pairs, and the goal is to generalize to new, unseen data Common supervised learning algorithms include linear regression, logistic regression, decision trees, and support vector machines
