What is Machine Learning?
Machine Learning is the application of Artificial Intelligence (AI) which helps to access the data and manipulate it at that form which software needs. this process of this application starts from the observation of the information of something and learn from there own experience without need any kind of instructions. Let's see the basic example of Machine Learning software.
For Example we have to create a game like a game of chess and want to perform all the possibilities of chess by the software itself. then we can follow two basic approaches:-
1. The first approach or you can say the method we add all kinds of possibilities of chess in software and it will take all the decisions on the basis of the instructions which you give and it will find the best output on the basis of input. which is practically not possible. So, this approach will take time and effort after your efforts maybe it will not give accurate output.
2. The second approach you can develop your software as per the basic rules and regulations of chess and let the software think by itself to find the best output according to their input. And you can also rewards the software of the basis of success and loss.
After that, the software will find automatically get the best move on the basis of the specific configuration of the board.
There are two types of learning system are as follow-
1. Supervised Learning - This is our first type of learning system. As per the name said we fully supervised our system which knows has all the pieces of information. In this system, we give both the input and expected output. with the help of input and output, it will classify and identify the processing for the future data and gives accurate output through trial and error. It also provides algorithms with known quantities in order to promote future decisions.
2. Unsupervised Learning - This is our second type of learning system. As per the name said this type of learning means the system has no knowledge about the output it only has input. with the patterns and groupings of the methods, it processes the input and gives the output. In this system you instruct the software about the inputs and software that don't have knowledge about the outputs then software finds the best relationship between input and output.
image src - machine learning image
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