Wine quality part 1 of 3: data analysis

In 2016, the 2015 global wine market was valued in €28.3 billion [6]. With such a large value, it makes sense to employ data science techniques to understand what physical and chemical properties affect wine quality. In this series of posts, I will work with the chemical components of the Vinho Verde wine (using the … Continue reading Wine quality part 1 of 3: data analysis

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Wale Akinfaderin on the mathematics of machine learning

I saw this LinkedIn article by Wale Akinfaderin on the mathematics of machine learning, and I agree to most what he wrote. I quote his article below and I would add optimisation as a must-to-know large field. Complementing what Wale said about this topic, I suggest subjects such as Linear and Semidefinite programming, Interior-point and simplex … Continue reading Wale Akinfaderin on the mathematics of machine learning

Visualising a Python algorithm profile

Writing code is a delicate task, as one misplaced comma leads to compiler displays weird error messages. A practice that I usually employ while coding is to write the whole algorithm as a combination of smaller components (snippets). A positive point for dividing it into components is the ability to debug individual parts of the code, as … Continue reading Visualising a Python algorithm profile