
AI Algorithm
Machine learning algorithms enable an AI system to learn from data and improve its performance over time.
An algorithm is designed to process data to create a specific outcome.
Rule-based algorithms rely on predefined rules and conditions to make decisions or perform tasks.
Machine learning algorithms enable an AI system to learn from data and improve its performance over time.
Examples
Rule-based algorithm example
A rule-based algorithm can be used to play the classic game of Rock-Paper-Scissors. The algorithm follows a set of predefined rules to determine the winner based on the choices made by the players. For example, if one player chooses rock and the other player chooses scissors, the rule-based algorithm will determine that rock wins. The algorithm applies a series of if-else statements to compare the choices and determine the outcome according to the rules of the game.
Machine learning algorithm example
:A machine learning algorithm can be trained to distinguish between images of cats and dogs. The algorithm is fed with a large dataset of labeled images of cats and dogs. It learns from the data and extracts features that differentiate cats from dogs, such as shapes, patterns, and textures. Once trained, the algorithm can take a new image and make a prediction on whether it contains a cat or a dog based on the patterns it has learned.