We explain what machine learning is with some easy-to-understand examples.
Learn how machine learning is being applied to human resources and social networks like LinkedIn.
Recruitment and human resources management are strategic processes that are becoming increasingly digital . But if we were already used to job portals and job interviews via Zoom , we will have to adapt to the changes that are coming.
Some companies are already using artificial intelligence and machine learning applied to human resources management. Your job may now depend on a machine , both for hiring and firing.
What is machine learning ?
Machine learning means automatic learning or machine learning.
The concept of machine learning is closely related to Artificial Intelligence (AI) . It seeks to ensure that devices or applications have their own intelligence , equal to or greater than consulting email list that of humans. To do this, they are programmed to react equally or more efficiently than humans.
But machine learning goes further, as it uses algorithms to enable artificial intelligence to learn from its experience. How? By giving machines the ability to identify patterns in massive amounts of data in order to make predictions and thus provide responses autonomously.
Machine learning is already part of our daily lives. For example, when we are registered on a streaming platform, it learns from our tastes and suggests recommendations to improve our experience.
Machine learning applied to chess
A good way to approach the knowledge of machine learning is to know how it works in the world of chess.
Artificial intelligence applied to the world of chess creates increasingly efficient computers capable of beating world champions in this discipline.
The computer software known as Deep Blue was the first to win a game against a world chess champion like Kasparov.
This software had access to extensive databases of moves and used an algorithm specially designed by a team of programmers and chess grandmasters. This algorithm was improved by using machine learning techniques . When it made a mistake, its code was reviewed and modified.
