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Pages
Posts
Neural Networks for the Curious Mind
Published:
Neurons are the basic building block of modern Machine Learning. Over the past two decades, Machine Learning systems have achieved remarkable success across numerous disciplines and industries, making understanding its fundamentals no longer a matter reserved for experts, but a general skill and a precious opportunity for curious minds. The goal of this blog is to explain Neural Networks in a step-by-step manner that doesn’t require a strong math background.
music
Lo que imaginabas - Input Permalink
Input band was a fleeting alternative rock project in which I participated in mid 2019. It was a short but substantial band, and I’m proud of everything we did together. Jorge Suarez and Jonathan Quevedo were the songwriters and minds behind the music. I participated mainly as intrumentalist and composing various bass lines. Other song snippets are available on the project’s instagram page.
Esto es Sagú - Son Sagú Permalink
Son Sagú is a family band with over 15 years of history. Dedicated to the Andean peasant folklore of Colombia’s central high plains, we specialize in Carranga. During the pandemic, we composed and recorded this original song, inspired by the landscapes and traditions of our parents’ and grandparents’ village.
Llámame Permalink
Llámame is a Vallenato (Colombian folk music) song with urban vibes. It was composed by my friend Jorge Suarez. This is my is my free interpretation, casually recorded on my phone.
publications
Drought forecasting using a hybrid neural architecture for integrating time series and static data
Published in Tackling Climate Change with Machine Learning workshop at ICLR, 2025
talks
teaching
[In Spanish] Imputación de datos hidrológicos usando algoritmos de Machine Learning
Workshop, Universidad Nacional de Colombia, Departamento de Ingeniería Civil y Agricola, 2025
This workshop aims to introduce third-year agricultural engineering students to the effective implementation of machine learning techniques for imputing missing values in hydrological data.