In the first post of this series, I made the case for having a Data Science methodology and shared 3 popular options. I hope you found those useful, but I’m also conscious that they are all old methodologies.
In that first post, I reviewed CRISP-DM, KDD & SEMMA methodologies. All of which were created during the heyday of Data Mining. Before the “AI winter” when exciting things were happening, but largely through using large stats packages or bespoke applications.(more…)