Supervised Learning

\Supervised learning is teacher-oriented learning in which a teacher teaches machine.

There are two types of Supervised machine learning

1. Classified supervised learning
2. Regressive supervised learning

Classified supervised learning:

   When the output of the supervised machine learning represents any category,

    that is called  Classified supervised learning.

for ex. Red, Blue, Curve, Straight, Sylendrical, etc.

Introduction to Machine Learning

INTRODUCTION:

Machine learning is a branch of science that deals with programming the system in such a way that it automatically learn and improve with experience. Here, learning means recognizing and understanding the input data and making a wise decision based on supplied data. 

It is very difficult to cater to all the decisions based on all possible inputs. To tackle this problem, algorithms ate developed. These algorithms build knowledge from specific data and past experience with the principles of statistics, probability theory, logic, combinatorial optimization, search, reinforcement learning, and control theory.

By machine, learning machine learns itself by recognizing any pattern or applying any other kind of technique. In machine learning, we teach the machine how to learn things.

The term Machine Learning was first introduced by"Auther Samuel". in 1959.

The developed algorithms form the basis of various applications such as-

1. Vision processing 
2. Language processing
3. Forecasting (e.g., stock market trends)
4. Pattern recognition 
5. Games 
6. Data mining 
7. Expert systems
8. Robotics.

There are three types of machine learning:

1. Supervised learning
2. Unsupervised learning
3. Reinforcement learning