MACHINE LEARNING

Have you ever dreamed of becoming a professor? I've always wanted to! If you feel that your dream was not satisfied then don't worry, teaching is  not only providing knowledge to humans, if you teach a machine something new ,that is also a part of teaching. More than providing data to the system, it is important for the system to understand the data you provide. This method where the machine understands the data provided by you is known as machine learning.

Is it done through coding? definitely not. Proving data to the system by statistical techniques is known as machine learning.

When i came to know about machine leaning, the first thing that came to my mind is ....What is the difference between Machine learning and Artificial intelligence.

It is very simple,

• Artificial intelligence is the method in which a system proceeds with the given task, this method would be considered smart. 
• Whereas machine learning is method of allowing the system to access the data and letting the machine to learn by itself.

Now we have a simple understanding about Machine Learning. Lets see the tasks of machine learning.

There are two categories of Machine Learning Tasks

• Supervised Learning
• Unsupervised Learning

Supervised Learning is nothing but providing partial data to the system for learning.

Little amount of input will be given to the system and the system learns about the input and output.

Unsupervised Learning is the method of leaving the system to learn by itself. The system has to learn all the mapping methods of input and output by itself.

There are three types in Supervised Learning

• Semi-supervised Learning :- In semi-supervised method, the computer will be given an incomplete set of data : Many sets of output will be missing and the system has to find those to perform training.  
• Reinforcement learning:- Data will be given in the form of feedback and the system has to gather input from those feedbacks.
• Active Learning:- Data will be provided within the given budget.

List of  approaches:-

• Decision tree learning
• Representation learning
• Genetic Algorithms
• Clustering
• Support Vector Machines
• Deep Learning