Hit Pause on AI: Time to Refresh the Basics

Author(s): Elangoraj Thiruppandiaraj

Originally published on Towards AI.

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Artificial Intelligence (AI) has quickly evolved from a buzzword to an important component in almost all industries today. It’s easy to get caught up in complex algorithms and fancy results it produces. However, it’s not good to overlook the importance of foundations or basics (especially statistics), which are the backbone of Generative AI and Data Science as a whole.

For any new starter to the field, the temptation is to move straight to model building and applying generative AI, but without a solid understanding of statistical principles, most of the projects are likely to fail. As an experienced Data Scientist, I or any expert will talk about the importance of statistics and it is a core foundation in understanding data, validating models, and making informed decisions.

In this article, I will revisit the statistical foundations that can help you become an industry-ready AI practitioner. Three topics in particular: descriptive statistics, probability theory, and inferential statistics. This can refine your skills and ensure that your AI models are not just sophisticated but statistically sound.

First step in Data Science project is understanding of your dataset. Descriptive statistics help us provide simple… Read the full blog for free on Medium.

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Published via Towards AI