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What is Machine Learning?

Arthur Samuel, firstly coined the term "Machine Learning". He defined the term as, "Field of study that gives computers the capability to learn without being explicitly programmed."

Explaining in layman terms, Machine learning means improving the process of learning for computers which is based on it's experiences to do a certain task without further guidance through programs. In other words, we can say that machine learns through initial program and feeds itself the data which obtained from the experiences while executing a particular task.

Let's take an example to understand this. A father and a baby went to a park to make the baby learn how to walk. Initially, the father hold the hands of his baby so that the baby can walk without tripping. As the baby can now stand on it's own legs, the father did not hold hands of the baby, thus the baby kept going on and tripped as stone hit the toes. The baby stood up and learned not to walk over stones. The next time baby faced the stones, he did not trip as he learned previously.
Same is the case with machine learning, it gives feedback to itself and this helps train the model.

The model which we trained can perform more efficiently than humans as the rate of error is reduced to great extent. ML and AI can be proved very beneficial in the fields where accuracy and precision both are important. Example: Health Industry, Stock market prediction, etc.

There are some pre-requisites to learn ML:
  1. Mathematical Skills:
    • Linear Algebra
    • Statistics
    • Probability
    • Calculus
    • Graph Theory
  2. Programming Skills:
    • Python
    • R Programming
    • MATLAB
    • C++
    • Octave
One can take chance if he/she chooses to go without Mathematics and learn as the concepts goes further, but learning Python is a must.

That's all for the brief of Machine Learning.
Hope it was worth investing time!

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