BigML is actively being used in many educational institutions across the globe thanks to our Education Program. We would like to present several personal stories of our ambassadors on how they inspire their students or classmates that are looking to become more data-driven with a solid understanding of Machine Learning with BigML. Today we start with Iván Robles, an engineer in telecommunications with a Bachelor Degree in Mathematics that teaches Machine Learning at the EAE Business School and at ICEMD Business School in Madrid, Spain, while working for the telecom company Orange. Let’s get to know Iván a bit more!
BigML: How did you get into working with data and Machine Learning in particular?
Iván Robles: I love Mathematics and just after I finished my degree, back in 2006, a friend of mine told me about a company that used math to solve real-world problems. The idea of using math and statistics in my daily life was pretty exciting to me, so I applied for an open position and started working with them. Before 2006 I did not know what Machine Learning was, but since that moment I haven’t stopped working and learning in this field. Machine Learning has the perfect mix between math and programming, which really got my attention, especially when I could see that I was helping solve real-world problems in several areas such as marketing, networks, finance, among others. Naturally, this is what I currently teach to my students.
BigML: How do you see that Machine Learning is transforming the world?
Iván Robles: My students come from different companies, some of them are working for big corporations and others are entrepreneurs that are building their own company, and in both scenarios, they do invest resources in applying Machine Learning techniques to learn how to make decisions based on data instead of human intuitions alone. This, as well as all the news related to governments from many countries investing in Machine Learning, tells me we are on the right path to transforming all types of organizations into data-driven companies. This was non-existent a few years ago, which tells us that Machine Learning is already transforming many industries. Some good examples are self-driving cars, chatbots that answer questions automatically, and human-robot interactions, but in my opinion, this is just the beginning.
BigML: How do you currently apply Machine Learning?
Iván Robles: I teach Machine Learning in two business schools located in Madrid, the EAE Business School, and ICEMD. My students have different profiles, so my goal is to showcase different domains where they can apply Machine Learning. For instance, in my classes I use BigML’s time series models to find out the number of calls that a given call center will receive per day, to prepare budgets, and to forecast sales of a given product, among other examples. With classification models like BigML’s decision trees and ensembles, we analyze and predict churn, as well as what clients will buy a certain product based on their characteristics, and other similar use cases.
BigML: What’s the biggest advantage of applying Machine Learning in your field?
Iván Robles: As a professor that teaches Machine Learning, the main advantage that I see is that many non-experts can actually enjoy the benefits of Machine Learning without having to figure out exactly how the math behind the algorithms work. For example, Machine Learning allows you to analyze in minutes a multitude of data and relationships among them that without it would take years. This inspires my students and it certainly has a very positive impact in their business life.
BigML: What is your goal using BigML?
Iván Robles: I use BigML in my classes because unlike other Machine Learning platforms, BigML is very intuitive and accessible. It is built to not only make data scientists more productive, but to enable anyone to harness the potential of Machine Learning. I always like to showcase real use cases to my students that can be solved by applying Machine Learning techniques, therefore, at EAE Business School and ICEMD we take advantage of the BigML Education Program to accomplish that goal.
BigML: How do you find BigML different from other Machine Learning platforms?
Iván Robles: BigML is very easy to use, understand, and interpret, thanks to your powerful visualizations. This is obviously very much linked to your mission of democratizing Machine Learning. I can tell this clearly works in my classes because some of my students don’t have any technical background, yet they do understand BigML and they see how they can use the results obtained with the Machine Learning models they create. They really like the fact that they don’t need to compute or calculate anything, as BigML does it for them. They only need to drag and drop their data and in as little as a few clicks get the results they are looking for to continue building their projects, which is pretty awesome.
For that matter, I do see the tremendous added value of the BigML platform and totally identify it with your vision of democratizing Machine Learning. The ease of use allows everyone to be able to use Machine Learning in their projects. And the powerful visualizations generate a “wow” effect. They are very interactive, and really help us see how the problems are solved by the rules suggested by the Machine Learning algorithms. Indeed, it’s very impressive!
BigML: What is the reaction of your students when they use BigML?
Iván Robles: My classmates love BIGML! They also have other subjects like programming languages for instance, but especially the business profiles find these subjects more difficult. However, with BigML it is different because the non-technical students often mention that BigML is their saviour, as they get the expected results very easily without being an expert in Machine Learning programming. On the other hand, the programmers also enjoy using BigML because they find that with your platform they don’t need to invest as much time and effort as they do with other tools. In fact, for both types of students, when they need to work on their final projects, they prefer easier and capable tools like BigML.
BigML: Any advice you would give to our readers to get started with Machine Learning?
Iván Robles: Start with BigML, and maybe you don’t need anything else! I mean it, BigML covers a large variety of use cases that can easily solve real-world problems with very good results applicable to plenty of organizations.
We hope Iván’s story inspired you to become a BigML Ambassador. Stay tuned for future blog posts to get to know more BigML community members and their personal stories. If you are not part of the BigML community yet you can change that right now, simply register here for free! Also, for those working in academia or still studying, feel free to join our Education Program and apply here to become a BigML Ambassador which also empowers you to promote our platform on your campus. Thanks for helping us in delivering #MachineLearning made beautifully simple for everyone!