We are living in an era where technological advances are common. According to AgingInPlace (2022), over the years, technology has revolutionized our world and daily lives. Technology plays an important role in society today. Technology’s advancements has given us brand new devices in recent decades, like smartwatches, tablets, and voice assistant devices. These devices have provided quicker ways to communicate through instant messaging apps and social media platforms. It has also made possible to do things like transfer money instantly and make purchases for everything from clothes, food delivery, groceries, furniture, and more.
tidymodels tidymodels is a suite of packages that make machine learning with R a breeze. R has many packages for machine learning, each with their own syntax and function arguments. tidymodels aims to provide an unified interface, which allows data scientists to focus on the problem they’re trying to solve, instead of wasting time with learning package syntax.
The tidymodels has a modular approach meaning that specific, smaller packages designed to work hand in hand.
As a data scientist, you need to distinguish between regression predictive models and classification predictive models. Clear understanding of these models helps to choose the best one for a specific use case. In a nutshell, regression predictive models andclassification predictive models` fall under supervised machine learning. The main difference between them is that the output variable—in regression is numerical (or continuous) while that for classification is categorical (or discrete).
