AI

Key differences between Artificial Intelligence (AI) and Machine learning (ML):

Artificial IntelligenceMachine learning

Artificial intelligence is a technology which enables a machine to simulate human behavior.

Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.

The goal of AI is to make a smart computer system like humans to solve complex problems.

The goal of ML is to allow machines to learn from data so that they can give accurate output.

In AI, we make intelligent systems to perform any task like a human.

In ML, we teach machines with data to perform a particular task and give an accurate result.

Machine learning and deep learning are the two main subsets of AI.

Deep learning is a main subset of machine learning.

AI has a very wide range of scope.

Machine learning has a limited scope.

AI is working to create an intelligent system which can perform various complex tasks.

Machine learning is working to create machines that can perform only those specific tasks for which they are trained.

AI system is concerned about maximizing the chances of success.

Machine learning is mainly concerned about accuracy and patterns.

The main applications of AI are Siri, customer support using catboats, Expert System, Online game playing, intelligent humanoid robot, etc.

The main applications of machine learning are Online recommender system, Google search algorithms, Facebook auto friend tagging suggestions, etc.

On the basis of capabilities, AI can be divided into three types, which are, Weak AI, General AI, and Strong AI.

Machine learning can also be divided into mainly three types that are Supervised learning, Unsupervised learning, and Reinforcement learning.

It includes learning, reasoning, and self-correction.

It includes learning and self-correction when introduced with new data.

AI completely deals with Structured, semi-structured, and unstructured data.

Machine learning deals with Structured and semi-structured data.