Introduction to Machine Learning

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Before jumping directly into what is Machine Learning lets starts with the meaning of individual words i.e. What is Machine and What is Learning.

  • A machine is a tool containing one or more parts that transform energy. Machines are usually powered by chemical, thermal, or electrical means, and are often motorized.
  • Learning is the ability to improve behaviour based on Experience.

What is Machine Learning? :-

According to Tom Mitchell, Machine Learning is
A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E

  • Task T is what machine is seeking to improve. It can be Prediction, Classification, Clustering etc.
  • Experience E can be training data or input data through which Machine try to learn.
  • Performance P can be some factor like improvements accuracy or new skills that Machine was previously unaware about of etc.

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Machine Learning itself contains 2 main components the Learner and the Reasoner.

  • Input/ Experience is given to the Learner that learn some new skills out of it.
  • Background Knowledge can also be given to Learner for better learning.
  • With the help of Input and Background, Knowledge Learner generates the Model.
  • The model contains the information about how he has learnt from the Input and Experience.
  • Now, the Problem/ task is given to Reasoner it can be Prediction, Classification etc.
  • With the help of trained Model Reasonar tries to generate the Solution.
  • Solution / Answer can be improved with adding additional input/ Experience Background knowledge.

How Machine Learning different from Standard Program? :-

In machine learning, you feed the computer the following things

  • Input [Experience]
  • Output [output corresponding to inputs]

And get Model/ Program as Output. With the help of this program, you can perform some tasks.

Whereas In Standard Program you feed the computer following things

  • Input
  • Program [how to process the input]

And get the Output a simple example can be to verify a number of Prime or not.

Machine Learning

REFRENCES :- Machine Learning By Tom Michell


Written by 

Principal Architect at Knoldus Inc

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