Predict ratings for #TidyTuesday board games
Use custom feature engineering for board game categories, tune an xgboost model with racing methods, and use explainability methods for deeper understanding.continue reading.
Use custom feature engineering for board game categories, tune an xgboost model with racing methods, and use explainability methods for deeper understanding.continue reading.
Get started with feature engineering for text data, transforming text to be used in machine learning algorithms.continue reading.
Learn how to train, explore, and understand an unsupervised topic model for text data.continue reading.
Using a tidymodels workflow can make many modeling tasks more convenient, but sometimes you want more flexibility and control of how to handle your modeling objects. Learn how to handle...continue reading.
Use spatial resampling to more accurately estimate model performance for geographic data.continue reading.
Get started with tidymodels workflowsets to handle and evaluate multiple preprocessing and modeling approaches simultaneously, using pumpkin competitions.continue reading.
Tune and evaluate a multiclass model with lasso regulariztion for economics working papers.continue reading.
Songs on the Billboard Top 100 have many audio features. We can use data preprocessing recipes to implement dimensionality reduction and understand how these features are related.continue reading.
In this screencast, focus on some tidymodels basics such as how to put together feature engineering and a model algorithm, and how to fit and predict.continue reading.
Learn how to evaluate multiple feature engineering and modeling approaches with workflowsets, predicting whether a person or the computer spoke a line on Star Trek.continue reading.
More xgboost with tidymodels! Learn about feature engineering to incorporate text information as indicator variables for boosted trees.continue reading.
Our new book in the Chapman & Hall/CRC Data Science Series is now complete and available for preorder!continue reading.
Early stopping can keep an xgboost model from overfitting.continue reading.
Models like xgboost have many tuning hyperparameters, but racing methods can help identify parameter combinations that are not performing well.continue reading.
Which Scooby Doo monsters are REAL?! Walk through how to tune and then choose a decision tree model, as well as how to visualize and evaluate the results.continue reading.
Predict prices for Airbnb listings in NYC with a data set from a recent episode of SLICED, with a focus on two specific aspects of this model analysis: creating a...continue reading.
Handling class imbalance in modeling affects classification metrics in different ways. Learn how to use tidymodels to subsample for class imbalance, and how to estimate model performance using resampling.continue reading.
Tune a decision tree model to predict whether a Mario Kart world record used a shortcut, and explore partial dependence profiles for the world record times.continue reading.
Walk through a tidymodels analysis from beginning to end to predict whether water is available at a water source in Sierra Leone.continue reading.
Are more CEO departures involuntary now than in the past? We can use tidymodels’ bootstrap resampling and generalized linear models to understand change over time.continue reading.