[R] 🔎 How I found external data for #1 Private LiderBoard solution on Kaggle

Web: https://www.reddit.com/r/MachineLearning/comments/vi6vef/r_how_i_found_external_data_for_1_private/

## Intro

**Competition**: [TPS January 2022](https://www.kaggle.com/competitions/tabular-playground-series-jan-2022), SMAPE as a target metric
**Special thanks**: [@ambrosm](https://www.kaggle.com/ambrosm) for the 1st place [notebook](https://www.kaggle.com/code/ambrosm/tpsjan22-10-advanced-linear-model-with-cci/notebook) and great disscussion on external data [here](https://www.kaggle.com/competitions/tabular-playground-series-jan-2022/discussion/302694)
📚 In this notebook we'll use:

* [Upgini](https://github.com/upgini/upgini#readme) \- Low-code Feature search and enrichment library for supervised machine learning applications.
📷

**Baseline model** in this notebook is based on u/ambrosm notebook (first place) with some minor changes:

* Feature engineering part was slightly changed, so we can prepare main features and external features separately; …

data kaggle machinelearning on