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It is used for picture identification, speech recognition, email filtering, Facebook auto-tagging, recommender systems, and many more activities.Machine Learning (ML) is a direction of computer science that enables computers to understand data in the same way that humans do.
Machine learning focuses on allowing computers to learn from their experiences without having to be explicitly programmed or involving humans.As our society moves closer to automating significant amounts of tasks currently handled by humans, students studying machine learning will have many prospects.
Machine learning is a limb of AI that integrates data with statistical methods to predict an output that may be used to provide meaningful insights.The breakthrough is based on the premise that a computer may learn from data (for example) to create correct results independently.
It also helps automate and speed up the building of data analysis models.
Various industries rely on large amounts of data to optimize operations and make informed decisions.
Machine Learning assists in the creation of models capable of processing and interpreting large amounts of complicated data and generating accurate results.
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.
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.