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Difference between Machine learning and Artificial Intelligence
Artificial Intelligence and Machine Learning play an important role in anything that is remotely related to Automation. AI and Machine Learning are the most advanced and popular technologies which are used for creating intelligent systems in different fields of engineering and science.
Although AI and ML are correlated, they are quite different from each other. AI is a wider concept that is used to build intelligent machines for the simulation of human thinking capability and behavior, whereas ML is an application of AI that allows machines to learn from data without being programmed explicitly.
Read this tutorial to find out more about AI and ML and how these two technologies are different from each other.
What is Artificial Intelligence?
Artificial Intelligence (AI) refers to a science where a non-natural element can be made intelligent. In simpler terms, an artificial man-made object can understand and think on its own. Artificial intelligence mainly deals with programming of computers to detect patterns in new data, make decisions based on user's inputs, and produce outputs based on the user's inputs.
AI can be divided into two main categories − narrow or general. Narrow AI is designed to perform a specific task, while general AI is designed to be capable of performing a wide range of tasks.
In AI, all the rules are not explicitly defined and it is expected by the developer that the machine learns these rules by experience, using a reward-punishment mechanism. Today, artificial intelligence is being used in designing self-driving cars, boats, object and facial recognition systems, and much more.
What is Machine Learning?
Machine Learning (ML) refers to ways by which a machine can learn without being programmed. In simple terms, machine learning is a data-driven application which can make its own decision based on varying inputs and can improve its decisions over time.
ML is a subset of AI that uses complex programs that can understand through experiences and create predictions. It is a concept that creates complex algorithms for huge data processing and supports results to its users.
In machine learning, the algorithms improve on their own by the frequent input of training data. ML algorithms use data to learn patterns and make predictions or decisions. The primary objective of machine learning is to learn data and build models from data that can be understood and used by humans. There are several types of machine learning, including supervised learning, unsupervised learning, and reinforcement learning.
Difference between Artificial Intelligence and Machine Learning
The following table highlights the important differences between Machine Learning and Artificial Intelligence −
Key |
Artificial Intelligence |
Machine Learning |
---|---|---|
Definition |
AI refers to the ability of a machine or computer system to perform tasks that would normally require human intelligence, such as understanding language, recognizing images, and making decisions. |
ML is a type of AI that allows a system to learn and improve from experience without being explicitly programmed. It articulates how a machine can learn and apply its knowledge to improve its decisions. |
Objective |
The objective of AI is to increase chances of success, accuracy of result is not at most priority. |
The objective of ML is to increase accuracy of result, success or failure is not at most priority. |
Concept |
The concept of AI revolves around making smart devices/computer. |
The goal of ML revolves around making a machine learn/decide and improve its results. |
Goal |
The goal of AI is to simulate human intelligence to solve complex problems. |
The goal of ML is to learn from data provided and make improvements in machine's performance. |
Development |
AI is leading to the development of such machines which can mimic human behavior. |
ML is helping in the development of self-learning algorithms. |
Solution |
The goal of AI is to find an optimal solution. |
The goal of ML is to reach to a solution, optimal or not. |
Achievement |
AI helps in attaining wisdom, to make smart devices. |
ML helps in gaining knowledge, to make informed decision. |
Conclusion
To conclude, the core concept of AI revolves around making smart devices and machines, while ML is all about making a machine to learn, decide and improve its results.
AI is a broad term that refers to the ability of a machine or computer system to exhibit intelligent behavior, while ML is a specific type of AI that involves training a system on data so that it can learn and improve over time.
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