Machine Learning (ML) in Human Resources represents a great advance in recruiting and talent retention, improving the experience of the employee, as well as people’s adaptation to teams or positions and it is also having an impact on motivation.
Tom Mitchell says that “A computer program is said to learn from experience ‘E’, with respect to some class of tasks ‘T’ and performance measure ‘P’ if its performance at tasks in ‘T’ as measured by ‘P’ improves with experience ‘E’.
To put it into simple words, if a computer program improves with experience, then we can say that it has learned.
The development of Machine Learning is the key to the optimal management of Big Data. This should not be underestimated considering that we refer to machines that learn and are able to predict behaviours, evaluate actions and analyse millions of data, in a matter of seconds.
This relationship can be reached in the following way:
– Supervised Machine Learning (SML) refers to the interpretation of the Big Data, previously classified, and therefore being able to predict behaviours 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 that 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 organisation, to boost their potential and to create a better working environment with something as simple as the storage of quality data, means we are definitely starting to live in the future.