Artificial Intelligence (AI) algorithms are a set of instructions that enable computers to learn and make decisions independently of human intervention. AI algorithms are more complex than general algorithms and are developed with different goals and methods. They work by taking in training data that helps the algorithm to learn, and then they complete their tasks using the training data as a basis.
There are three major categories of AI algorithms: Supervised Learning, Unsupervised Learning, and Reinforcement Learning.
• Supervised learning is a type of machine learning where the algorithm is trained on labeled data. The algorithm learns to recognize patterns in the data and can then apply those patterns to new, unlabeled data.
• Unsupervised learning is a type of machine learning where the algorithm is trained on unlabeled data. The algorithm learns to recognize patterns in the data without any prior knowledge of what those patterns might be.
• Reinforcement learning is a type of machine learning where the algorithm learns by interacting with its environment. The algorithm receives feedback in the form of rewards or punishments for certain actions, and it learns to take actions that maximize its rewards over time.
AI algorithms are used in various applications such as facial recognition, search engines, social media algorithms, and more. They help businesses track their advertising campaigns performance by measuring metrics such as conversion rate, cost per acquisition (CPA), customer acquisition cost (CAC), click-through rate (CTR), bounce rate, website sessions, pages per session, and return on ad spend (ROAS).