What is the basic difference between Artificial intelligence and Machine learning.
Artificial Intelligence
Computer Science Engineering
1936
Krishav
Artificial intelligence and machine learning are the part of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems.
AI is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior, whereas, machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.
Artificial intelligence is comprised of two words "Artificial" and "intelligence", which means "a human-made thinking power." Hence we can define it as,
Artificial intelligence is a technology using which we can create intelligent systems that can simulate human intelligence.
Based on capabilities, AI can be classified into three types:
Machine learning enables a computer system to make predictions or take some decisions using historical data without being explicitly programmed.
Machine learning is a subfield of artificial intelligence, which enables machines to learn from past data or experiences without being explicitly programmed.
Machine learning is being used in various places such as for online recommender system, for Google search algorithms, Email spam filter, Facebook Auto friend tagging suggestion, etc.
It can be divided into three types:
Some of the basic differences between Artificial Intelligence (AI) and Machine learning (ML) are
Artificial Intelligence : It includes learning, reasoning, and self-correction.
Machine learning : It includes learning and self-correction when introduced with new data.
Artificial Intelligence : AI system is concerned about maximizing the chances of success.
Machine learning : Machine learning is mainly concerned about accuracy and patterns.
Artificial Intelligence : The main applications of AI are Siri, customer support using catboats, Expert System, Online game playing, intelligent humanoid robot, etc.
Machine learning : The main applications of machine learning are Online recommender system, Google search algorithms, Facebook auto friend tagging suggestions, etc.
Artificial Intelligence : AI is working to create an intelligent system which can perform various complex tasks.
Machine learning : Machine learning is working to create machines that can perform only those specific tasks for which they are trained.
Artificial Intelligence : AI completely deals with Structured, semi-structured, and unstructured data.
Machine learning : Machine learning deals with Structured and semi-structured data.
Artificial Intelligence : On the basis of capabilities, AI can be divided into three types, which are, Weak AI, General AI, and Strong AI.
Machine learning : Machine learning can also be divided into mainly three types that are Supervised learning, Unsupervised learning, and Reinforcement learning.
Artificial Intelligence : Machine learning and deep learning are the two main subsets of AI.
Machine learning : Deep learning is a main subset of machine learning.
Artificial Intelligence : The goal of AI is to make a smart computer system like humans to solve complex problems.
Machine learning : The goal of ML is to allow machines to learn from data so that they can give accurate output.
Artificial Intelligence : AI has a very wide range of scope.
Machine learning : Machine learning has a limited scope.
Artificial Intelligence : In AI, we make intelligent systems to perform any task like a human.
Machine learning : In ML, we teach machines with data to perform a particular task and give an accurate result.
Artificial Intelligence : Artificial intelligence is a technology which enables a machine to simulate human behavior.
Machine learning : Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.
Artificial intelligence is used to develop a wise and savvy computer system that can mimic just like a human, and solve complex problems. Machine learning enables machines to learn from incidents and data to fetch the correct output.