Machine Learning - Machine Learning Introduction

In this video we are going to discuss machine learning introduction

So machine learning is a field of computer science that gives computer system one ability

to learn from data and without being explicitly programmed. So there is a new arena in our computer science

Nowadays it is very much important and very much attractive for all the computer science

people and here the computer science is making one computer enabled to learn from data

without having any explicit programming. The name machine learning was coined in the year 1959 by Arthur Samuel

Now if you consider these three different domains, if you consider, then you see the machine

learning is coming in the intersection of these two domains and data science is actually

falling in the intersection of all the three domains. Machine learning is a system which can do automatic acquisition and integration of knowledge It is that branch of artificial intelligence that deals with the construction of system that

can learn from data. So this word is the main thing in our machine learning

That means the computer system will have some artificial intelligence so that it can learn

from the given data set. methods that can automatically detect patterns in data and then to use these patterns

to predict future data. So, this machine learning will judge or will explain or we'll yze our given data and

then from the given data it will try to find one pattern which is occurring in that particular

data set and then from the pattern it can also go for forecasting for the coming days

learning can predict the future based on the past so data which will be given to the

machine learning system obviously that is the past data and from where the

machine learning will predict for the future computer programs that automatically improve their performance through experience Now the question can be asked why machine learning Automatically adapt and customize to individual

users. So for individual users recommend this machine learning can have its own specific applications

So personalized news, mail filters, movie, book recommendations. So, these are the very common machine learning applications we're enjoying nowadays

And mail filters, you know, whether a mail is a spam mail or not, that can be detected

by this machine learning applications. So, discover new knowledge from huge amount of data as an example we can go for the market

ysis and trending. repetitive monotonous tasks of humans which require intelligence and experience

So this particular machine learning can perform those repetitive monotonous task which require

some intelligence and also some experience So in those cases the human being may be replaced by the machine learning applications So recognize signature or handwritten characters So it is

it requires some intelligence, it requires some experience and it is monotonous and repeatedly

the persons they used to do such work. So that work can be done by the machine learning

applications. Driving a car or flying a plane. Rapidly changing, phenomenon. So, under this we can go for credit scoring, financial modeling, diagonesis

and fraud detection. No human expertise, industrial manufacturing control, mass spectrometer ysis, and drug design. So in case of drug design, this machine learning is having

very important and serious applications. So here in this particular session, we have understood

that what is machine learning and in which domain are there under which the intersection

the machine learning is there and why the machine learning is playing such a wider role

in our daily work. Thanks for watching this video