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”
Here,

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.

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.