The Difference Between Artificial Intelligence And Machine Learning

The Difference Between Artificial Intelligence And Machine Learning
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Written by Sagar RabidasNovember 11, 2021
6 min read
Artificial Intelligence
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Sagar Rabidas

Software Developer

In this blog, we will discuss the difference between Artificial Intelligence and machine learning.

About Artificial Intelligence

Artificial intelligence (AI) is a huge-ranging department of computer technological know-how worried with constructing smart machines capable of completing tasks that commonly require human intelligence.

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About Machine Learning

Machine learning (ML) is a branch of Artificial Intelligence (AI) and computer science which focuses on the use of facts and algorithms to imitate the way that humans study, regularly enhancing its accuracy.

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Difference between AI and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are two very available words at this time, and often seem to be used interchangeably. They are not quite the same thing, but the perception that they are can sometimes lead to some confusion.

So I write some piece of the word for different that. Both terms crop up very frequently when the topic is Big Data, analytics, and the broader waves of technological change which are sweeping through our world.

In short, the best answer is that: Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”. And, Machine Learning is a current application of AI-based around the idea that we should just be able to give machines access to data and let them learn for themselves.

Artificial Intelligence

  1. Artificial Intelligence is a technology that enables a machine to simulate human behavior.
  2. The goal of AI is to make a smart computer system like humans to solve complex problems.
  3. In AI, we make intelligent systems to perform any task like a human.
  4. Machine learning and deep learning are the two main subsets of AI.
  5. AI has a very wide range of scope.
  6. AI is working to create an intelligent system that can perform various complex tasks.
  7. AI system is concerned about maximizing the chances of success.
  8. The main applications of AI are Siri, customer support using catboats, Expert System, Online game playing,
    an intelligent humanoid robot, etc.
  9. Based on capabilities, AI can be divided into three types, which are, Weak AI, General AI, and Strong AI.
  10. It includes learning, reasoning, and self-correction.
  11. AI completely deals with Structured, semi-structured, and unstructured data.

Machine Learning

  1. Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.
  2. The goal of ML is to allow machines to learn from data so that they can give accurate output.
  3. In ML, we teach machines with data to perform a particular task and give an accurate result.
  4. Deep learning is the main subset of machine learning.
  5. Machine learning has a limited scope.
  6. Machine learning is working to create machines that can perform only those specific tasks for which they are trained.
  7. Machine learning is mainly concerned with accuracy and patterns.
  8. The main applications of machine learning are the Online recommender system, Google search algorithms, Facebook auto friend tagging suggestions, etc.
  9. Machine learning can also be divided into mainly three types are Supervised Learning, Unsupervised Learning, and Reinforcement Learning.
  10. It includes learning and self-correction when introduced with new data.
  11. Machine learning deals with Structured and semi-structured data.


Thanks for reading our blog.

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machine learning
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AI vs ML
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