Introduction to Machine Learning

There is also a category called Semi-Supervised Machine Learning.

Before going into the categories, let us explore what is the Machine learning.

So far, we have used many software applications in our day to day life. But with time, the data stored in these applications has increased enormously. Now a days from schools to hospitals, every one is using a computer to store the details of their respective customers. In case of schools, every year 100's of students join as well as graduate, all their details are saved in a database. The data in this database has increased exponentially with time. This huge amount of data is the key asset for Machine Learning.

Machine Learning is an art of making the machines intelligent with out programming explicitly. What it means is that you need not handle all the possible scenarios when you are writing the code, the machine has to predict the output. For the purpose of predict the outcomes, there are many algorithms/techniques  designed for Machine Learning.

The key elements in any machine leaning algorithms are as follows :

1. Process the data 
2. Identify which type of problem it is like regression, classification etc.
3. Create a model
4. Test and Improve the model with the experience