Machine Learning - Basics and classification

• Machine Learning is giving ability to machines to learn/program on it own.
• Machine learning is not restricted to Artificial Intelligence. It is having many applications in various filed, Recommendations System raging from data mining, rating system to automation of house hold activities.
• Machine is said to be 'learning', if its performance improves with experience. 

Classification of Machine Learning (ML):

1. Supervised ML.
2. Unsupervised ML.

1. Supervised ML

• Known Sample data sets are given. (Test Passed / Failed )
• Regression : Continuous value .
• Classification : Discrete value

2. Unsupervised ML

• Data set don't have any label (like Passed /Failed)  
• Just data set is given and algorithm will divide it in cluster.
• As we are not specifying what data belong to what segment/ cluster its unsupervised learning.
• We have to derive structure from unknown data.