You will have heard about Artificial Intelligence (AI) and if you do not know, then I will tell you that once you fall in it also.
So Machine Learning; Artificial Intelligence is a branch in which we program computer or machine in such a way that the user can work with this machine as it works, and in this process, the computer will be able to get its own data from the first Works and gives its performance.
The process of programming a machine or computer is called training, in which we give some data to the machine and the machine stores this data in its database which is called learning and once the machine stores this data with you Then it is called Trained Machine, so now the machine has its own job, Museum does its job on this data.
It is also sometimes called Inductive Learning. Inductive learning is a learning that is derived from observation and knowledge (rules and conclusions). In other words, inductive learning is a process of learning through examples.
Let's understand this through an example - Suppose you own a grocery store and you want to order a soap for your shop, then how will you know how much you want to order soapo See the records of the previous months, how much soap is sold every month, and if you order the next month accordingly, then this process is done with the machine, Receive data offer that sold many soaps in the past months and Machine means that Learn this data is the order of the store in the database and how Sabuno for estimates on the basis of this data the next month.
Now you should be thinking that this work can be done either by our Laptop or PC, i.e. to store the data, so friends, this work depends on how much and what level of work we want to get from it because If we want to work on a very small level then it can be from our Laptop or PC, but if we have to guess something then we need a lot of data for that which is not our Laptop or PC process.
So friends, I'm not talking about small data. I am talking about big data like Google has data from all over the world and every minute people are putting new information here and in the next few years this data will be so much that it will be done by the person If this cannot be handled by Google, then Google will not be able to handle this data and then the ML machine will learn how to handle this data.
How Machine Learning works.
Today, machine learning is used for many types of work. Problem such as Face Recognition is very difficult for humans to write programs. We do not know if writing a program is because there are many types of faces in this world and if we sit for writing programs for every face then it will be very difficult. So we get help that machine learning.
We collect a lot of data which is analyzed by analyzing a lot of faces, then we put this data into an algorithm, then this algorithm and data are given to the machine, which is created by ML program. This program is very different from hand written programs, it keeps many types of characters, millions of numbers, which can be processed easily by using special machine and can be used for face recognition.
There are mainly three types of machine learning algorithms
Supervised Learning: In this learning, as an input, the labeled data consists of an example and an answer. And then the algorithm estimates the correct result based on these labeled data. Supervised learning is the case of two.
Regression:
Classification: Unsupervised Learning: This is not labeled as input and no answer is given. In this, the algorithm has to guess based on the data. Unsupervised learning is the case of two.
Clustering:
Association: Reinforcement Learning: In this learning, the algorithm uses its own Reward and Feedback as input.
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