There’s been a lot of buzz lately about Artificial Intelligence (AI) and Machine Learning (ML). But what’s the difference between the two? In this article, we will break it down for you and explain the key differences.
Artificial Intelligence is a process of programming computers to make decisions for themselves. This can be done through several methods, including rule-based systems, decision trees, genetic algorithms, artificial neural networks, and fuzzy logic systems. Machine Learning, on the other hand, is a process of teaching computers to learn from data. This is done by feeding the computer a large amount of data and then letting it find patterns and relationships in that data. It can create predictive models, cluster data, and perform classification tasks.
So what’s the difference between Artificial Intelligence vs Machine Learning? Artificial Intelligence is more focused on the process of making computers make decisions for themselves. It can be used to create rule-based systems, decision trees, genetic algorithms, artificial neural networks, and fuzzy logic systems.
Machine Learning is more focused on the process of teaching computers to learn from data. It can be used to create predictive models, cluster data, and perform classification tasks.
Artificial Intelligence is a process of making computers make decisions for themselves, while Machine Learning is more focused on the process of teaching computers to learn from data. Artificial Intelligence and Machine Learning can create predictive models, cluster data, and perform classification tasks.
