Machine Learing

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 change when exposed to new data.

"A computer program is said to learn from experience E with respect to some task T and some performance measure P,
 if its performance on T, as measured by P, improves with experience E.” 
 -- Tom Mitchell, Carnegie Mellon University 

So if you want your program to predict, for example, traffic patterns at a busy intersection (task T), you can run it through a machine learning algorithm with data about past traffic patterns (experience E) and, if it has successfully “learned”, it will then do better at predicting future traffic patterns (performance measure P).

ML solves problems that cannot be solved by numerical means alone. 

To break down the definition for easier understanding I should mention some factors that we should know as follows:

1. Method means technique or way to do
2. Data means set of information
3. Existing data means data already we have for any task.
4. Algorithm - Step by step set of operations/command to be performed
5. Automatically – Something is done or gained without working again.
6. Model - Data schema that learn from data iteratively