What is Machine Learning ?

What is Machine Learning?

Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can teach themselves to grow and change when exposed to new data. Making long definition to short , this is Algorithm. ML solves problems that cannot be solved by numerical means alone.

Why there is rising interest In Machine Learning?

To manage lot of data and popularity of Bayesian Analysis

High-Value predictions that can guide better decisions and smart action in real time without human interaction

 Humans can typically create one or two good models a week; machine learning can create thousands of models a week.

Types :

Supervised Learning and Unsupervised Learning

SUPERVISED LEARNING:

• Arranging the same type of fruits at one place is easy now.
• Your previous work is called as training data in data mining.
• So you already learn the things from your train data, this is because of response variable.
• Response variable mean just a decision variable.
• You can observe response variable below (FRUIT NAME) .

NO.	SIZE	COLOR	SHAPE	FRUIT NAME
1	Big	Red	Rounded shape with a depression at the top	Apple
2	Small	Red	Heart-shaped to nearly globular	Cherry
3	Big	Green	Long curving cylinder	Banana
4	Small	Green	Round to oval,Bunch shape Cylindrical	Grape

• Suppose you have taken an new fruit from the basket then you will see the size , color and shape of that particular fruit.
• If  size  is Big , color is Red , shape is rounded shape with a depression at the top, you will conform the fruit name as apple and you will put in apple group.
• Likewise for other fruits also.
• Job of groping fruits was done and happy ending.
• You can observe in the table that  a column was labeled as “FRUIT NAME” this is called as response variable.
• If you learn the thing before from training data and then applying that knowledge to the test data (for new fruit), This type of learning is called as Supervised Learning.
• Classification comes under supervised learning.

UNSUPERVISED LEARNING

• Suppose you had a basket and it is filled with some different types fruits, your task is to arrange them as groups.
• This time you don’t know anything about that fruits, honestly saying this is the first time you have seen them.
• so how will you arrange them.
• What will you do first???
• You will take a fruit and you will arrange them by considering physical character of that particular fruit. Suppose you have considered color.
• Then you will arrange them on considering base condition as color.
• Then the groups will be something like this.
• RED COLOR GROUP: apples & cherry fruits.
• GREEN COLOR GROUP: bananas & grapes.
• so now you will take another physical character such as size .
• RED COLOR AND BIG SIZE: apple.
• RED COLOR AND SMALL SIZE: cherry fruits.
• GREEN COLOR AND BIG SIZE: bananas.
• GREEN COLOR AND SMALL SIZE: grapes.
• job done happy ending.
• Here you didn’t know learn anything before ,means no train data and no response variable.
• This type of learning is know unsupervised learning.
• Clustering comes under unsupervised learning.