All my life I have thought that being a generalist was something bad. Throughout my life I have learned juggling, guitar, debate, learned multiple languages, gone deep on diverse topics from neuroscience to economics, and many many more.
In this hyperspecialized world that is something to fear and not to be proud of. But I have seen how all of those skills I have acquired have helped me in many ways. Learning how to juggle has given me the ability to know where my hands are at all time, so I rarely drop objects. Learning English, Italian and German has allowed me to meet people and understand them in their own language, melting the initial language barrier. There are many words in these languages that do not exist in Spanish and that has opened my mind to different world models that languages provide.
In Deep Learning there is a concept called transfer learning, which consists of using a previously trained model (usually very big) and adjust it with the target classes that need to be classified. Similarly, I constantly see applications of apparently distant knowledge to problems. Essentially, my life experience has provided me with plenty of points of view and enough analogical thinking to understand the subtle connections between diverse problems.
This book reassured that being a generalist is not only good but it is a desired trait that when combined with a growth mindset will take me on a journey to accomplish great things.
I'm a Data Scientist in the Environmental and Fleet Services for Gruppo Hera. I have led the AI initiatives for the identification and classification of abandoned waste both from a project management and hands-on code roles. I also provide technical criteria for the department's AI and Data related projects.
Mostly specializing in Computer Vision for use in industry, but I consider myself a hybrid often serving as a bridge between technical and business teams. I love to do deep dives into datasets in order to extract valuable insights. Ultimately, what I enjoy the most is asking questions to the dataset and using statistical analysis/ML tools to answer them.