Machine Learning
Matías Creimerman - Buenos Aires, Argentina - 2019-09-25

Machine Learning is a discipline of artificial intelligence that creates systems that learn by their own means.

That is, this learning is the identification of patterns in a context of billions of data. What learning machines do is process the data and adapt the algorithms to predict the results.

Suppose we want to identify which customers can potentially lose. If we had all the history of customer information and all interactions with it, we could decompose the information in a useful way to know what can happen with that customer. The information process is iterated and compared until it concludes in results that may be useful.

The most important of these systems is that they don’t need human interaction and learn by their own means.

In the future of work, machine learning will be a common operation in all businesses. We must be prepared to understand its use and the benefits we can get. Day by day, these systems are increasingly powerful and predict results with greater accuracy.

It’s essential to be able to design and understand data in large volumes in order to achieve more powerful learning machines. Data is its fundamental piece.

In the future of work we have to adapt to delegate the treatment of volumes of data and how to consult them with the learning machines. They save us time and reasoning processes.

For businesses with large volumes of customers and information, it’s and will be an important pillar in the future of work. It’s up to us how we are going to use it to take advantage of it.

This content is property of Matias Creimerman
Any misuse of this material will be punishable
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
Creative Commons License