5, 10 or 20 seats+ for your team - learn more
Imagine you’re an academic researcher working on a project for predicting trends in the U.S. government’s policy-making priorities. Using modern techniques for text data feature engineering, you’ll fit a set of models, subsample the training data to minimize bias, evaluate the models’ performance using a test-set of observations, and leverage a tidy workflow to explain how a model generates specific predictions.
This liveProject is for intermediate R programmers who know the basics of data science and have used the tidymodels framework for creating ML models. To begin these liveProjects you will need to be familiar with the following:TOOLS
In this liveProject, you’ll be adept at using multiple ML feature engineering techniques, subsampling procedures, and model explanation using the tidymodels framework.
geekle is based on a wordle clone.