The good old clustering analysis techniques present some differences when applied to time series. So many to discuss in one simple post. However, I will do my best to provide some examples of two basic approaches for doing time series analysis [6min read].
Nobody has doubts about the importance for humankind of the PANINI sticker album for the FIFA World Cup. From a mathematical point of view, several interesting questions arise. How much money do they need to spend? How many other collectors do they need to interact with? What if a sticker pack had 6 stickers instead of 4? Rodralez, from LABSIN developed an app for answering these and other questions [3min read].
Sometimes the standard splitting techniques used for testing your machine learning models can underestimate the generalization performance of the model. In this post, I expose some of the most common approaches for splitting your data beyond the classical random split approach. [5min read]
The idea of making art with code is not new, but what about Data? Can data be a work of art? Well, the truth is that thanks to conceptualism, it is possible. Trust me! [4min read]
DVC provides the elements for managing machine learning pipelines using git repositories as a backend. If you use git for tracking your machine learning experiments, you will feel comfortable with DVC.[9min read]
