Difference between Machine learning and Artificial Intelligence

What are the differences between Machine learning and Artificial Intelligence.

Artificial Intelligence and Machine Learning they both are the terms of computer science and data science.

In this article we discusses about the differences between the machine learning and artificial intelligence on the basis of different points:



Artificial Intelligence :

The word Artificial Intelligence composed of two words “Artificial” and “Intelligence”. Artificial means something which is made by human or non natural thing and Intelligence refers to ability to understand or think.

There is a misunderstanding that Artificial Intelligence is a system, but in reality AI is not a system rather AI is implemented in the system. There are many definitions of AI, one definition can be “It is the study of how to train the computers so that computers can do things which at present human can do better.”

Features of Artificial Intelligence

  1. Speech recognition,
  2. decision-making,
  3. visual perception

, The human intelligence system also works in the same way. Translation between languages is another feature which we discuss in the next tutorials.

Applications of artificial Intelligence

  1. Automation-Artificial Intelligence
  2. Business- Artificial Intelligence
  3. Self Driving Vehicles
  4. Health Sector

Machine Learning :

Machine Learning is the learning process where machine can learn by its own without being explicitly programmed by the programmer. It is a part of  an Artificial Intelligence . It allows the system the ability to automatically learn and improve from experience that it acquires from past and present.

machine learning difference

Here we can generate a model or a program by integrating input and output data of that program. Defining machine learning in simple language “Machine Learning is said to learn from experience E with respect to some class of task T and a performance measure P if learners performance at task in the class as measured by P improves with experiences.”


Examples of machine learning

Machine learning is widely used in todays life in almost every aspect. One of the most well-known common examples is Facebook’s News Feed. The News Feed uses machine learning to engrave each member’s feed. If a member frequently read or like a particular friend’s posts, then the News Feed will start to show more relevant post which he has read earlier.

Types of Machine learning

  1. Decision trees
  2. K-means clustering
  3. Neural networks
  4. Reinforcement learning


The main difference between AI and ML are:



AI stands for Artificial intelligence, which is the creation of intelligent machine that can react and work like human beings

ML stands for Machine Learning which is application of artificial intelligence (AI). It  provides systems the ability to automatically learn, improve from experience without being explicitly programmed

The main target of AI is to increase chance of success and not accuracy.

The main target of ML is to increase accuracy, since it doesn’t care about success

It work on the basis of computer program that does smart work

It simply collect the data and learn from that data.

The main goal is to simulate natural intelligence to solve taugh problem

The main goal is to learn from data on certain task to in order to maximize the performance of machine on this job.

It is decision making.

ML lets system to learn new things from data.

It allows the system to mimic human to respond behave in a circumstances.

It model involves in creating self learning algorithms.

AI will go for finding the optimum solution.

ML do not go for finding the optimal solution rather it go for only solution.

AI leads to intelligence development.

Machine learning leads to knowledge development.


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