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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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From HBR: How to Integrate Data and Analytics into Every Part of Your Organization

A friend of mine recommended an interesting article from the Harvard Business Review (HBR) about using Data and Analytics across different parts of organisations (I have copied the content below). It is worth to remember that there are methodologies to correctly employ data for business strategies. See, for instance, the CRISP-DM methodology illustrated below.   … Continue reading From HBR: How to Integrate Data and Analytics into Every Part of Your Organization

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

8 Ways Machine Learning Is Improving Companies’ Work Processes 

Interesting article from the Harvard Business Review Today’s leading organizations are using machine learning–based tools to automate decision processes, and they’re starting to experiment with more-advanced uses of artificial intelligence (AI) for digital transformation. Corporate investment in artificial intelligence is predicted to triple in 2017, becoming a $100 billion market by 2025. Last year alone saw $5 … Continue reading 8 Ways Machine Learning Is Improving Companies’ Work Processes