The AI revolution, as a continuation of the BI revolution, caused companies to acquire, ramp up, centralize, and deepen their data analytics, data science, and data
Close your eyes and imagine a machine learning production pipeline (come on, you can do it). What do you see? Oh yes, data sources; a data
Data has been a hot topic of discussion for years now. As organizations create and collect more and more data, it's key that they use it
In the world of machine learning, developers can create independent environments for projects easily. It only takes a few clicks to set and fit models in
In part one of this two-part series, we explored basic models and data enrichments for our hit song classifier. In this article, we will try to
Everyone knows that having a large number of loyal customers is the key to the success of a business. This statement is even more significant for
It comes as no surprise that the music industry is tough. When you decide to produce an artist or invest in a marketing campaign for a
Feature selection algorithms are increasingly growing in significance. In this article, we will cover (and compare) two popular feature selection methodologies - Filter and Wrapper.
The whole idea behind interpretable and explainable ML is to avoid the black box effect.