Machine Learning (ML) in the area of Human Resources represents a great advance in talent search and retention, improving the employee experience, as well as people adaptation to teams or positions and even having an impact on motivation.
Tom Mitchell defines it as a “computer program that learns through experience E about some kind of tasks (T) and performance measure (P), if its performance in tasks in (T), measured by P, improves with experience E”.
Even in Human Resources, the development of Machine Learning is key to optimal management of Big Data. This gear should not be underestimated considering that we refer to machines that learn and are able to predict behaviors, evaluate actions and analyze, in a matter of seconds, millions of data.
This relationship can be reached in the following way:
– Supervised Machine Learning (SML) refers to the interpretation of Big Data, previously classified, and thus be able to predict behaviors and trends.
– Unsupervised Machine Learning (UML) refers to the interpretation of millions of data and unclassified records, which intensifies the development of algorithms and artificial intelligence systems (AI).
Machine Learning Vs Deep learning
Going a step further is deep learning, a concept encompassed within machine learning that works differently. On this occasion, the main difference between these learning methods is the level of detail, in deep learning is greater, which points to the resolution and analysis of more complex situations. A better understanding of the employees’ engagement in the organization, boost their potential and create better working environments with something as simple as the storage of quality data, is start living in the future.