Algorithm

Algorithms can range from simple instructions, like sorting a list of numbers, to complex processes used in machine learning models, such as training a neural network. They are typically expressed in a formal language that a computer can understand and execute. The efficiency of an algorithm is often measured by its time complexity (how long it takes to run as the input size grows) and space complexity (how much memory it requires). In AI, algorithms are used for a wide range of tasks, including data analysis, pattern recognition, prediction, and decision-making. Choosing the right algorithm is crucial for achieving optimal performance and accuracy in AI applications. Examples include gradient descent for optimizing model parameters, decision trees for classification, and search algorithms like A* for pathfinding.