Machine Learning is changing the problem-solving dynamics of the Hospitality Industry by Fernando Acevedo

machine_learning

My name is Fernando Acevedo and I am from Madrid, Spain. My background is in Hospitality & Tourism. For the past two years I have been working for Madrid’s Hotel Owner Association (AEHM), which is the body representing the hotel sector in the region. You are probably wondering what this has to do with Data Science and Machine Learning?

During my time spent working side by side with the hoteliers and the companies that supply them, I realized how Data Science and Machine Learning are changing the problem-solving dynamics of the Hospitality Industry and yet, how scarce is such talent available in the Industry, at this moment.

I though it no more, I singed up for IE’s XL Data Science Bootcamp.

Last week has been week number 10 in the programme and I cannot believe it is almost over!! Time really flies and every week we discover a new Machine Learning model or a new way of getting things done.

A knowledge that will prove to be extremely useful in any situation, since Data Science is applicable in any industry.

During the week, we learned how to build Artificial Neural Networks, the algorithm that resembles the most to a human brain: a network of nodes working together capable of “learning” from the information they process, without the need of being programmed with any specific rule. In fact, it is the most useful model for image recognition.

To be more specific, I can think of hotels using this algorithm to detect regular fraudulent clients, who travel from one luxury hotel another, enjoying all the comforts and leaving without pay in the end, which believe it or not, still a difficult task for us today.

In addition, we also learned about Apache Spark, an SQL-like language that is useful to manipulate Data Frames in Python and the way it is making the life of data scientist easier, because it can store data in real time, but more importantly, it reduces drastically the time to run machine certain machine learning algorithms, such as clustering.

However, and certainly for all of us, the focal point this week has been the last preparations for our Demo Day presentations, the moment of truth, where all our efforts and all that we have learned will have to be demonstrated in a mere fifteen minutes, a true challenge and something impossible to achieve without my teammates Tania Vasilikioti and Inna Saboshchuk.

I am personally looking forward to it!!!