Explore our demo notebooks to understand various use cases of Population
Dynamics embeddings.

| Notebook | Description |
|---|---|
| [Custom boundary aggregation Colab](https://colab.research.google.com/github/googlemaps-samples/insights-samples/blob/main/population_dynamics_insights/notebooks/worldpop_weighted_custom_boundary_aggregation/pdi_worldpop_weighted_custom_boundary_aggregation.ipynb) | Demonstrates how to aggregate S2 cell embeddings into custom polygonal boundaries using Earth Engine population data to create population-weighted machine learning features. |
| [Economic forecasting Colab](https://colab.research.google.com/github/googlemaps-samples/insights-samples/blob/main/population_dynamics_insights/notebooks/time_series_forecasting/pdi_economic_forecasting_example.ipynb) | Demonstrates how to integrate S2 cell embeddings with Data Commons economic data to train machine learning models for county-level time-series forecasting. |
| [Nowcasting Colab](https://colab.research.google.com/github/google-research/population-dynamics/blob/master/notebooks/pdfm_nowcasting.ipynb)\* | Uses past and partial present-day data for a county-level target variable to predict outcomes for remaining counties. |
| [Superresolution and imputation Colab](https://colab.research.google.com/github/google-research/population-dynamics/blob/master/notebooks/pdfm_superresolution_and_imputation.ipynb)\* | Helps train a model at the county level on a target variable to predict at the ZIP code level. Also demonstrates imputation (training on 20% of ZIP codes and predicting for the remaining 80%). |
| [Nighttime lights prediction with Earth Engine Colab](https://colab.research.google.com/github/google-research/population-dynamics/blob/master/notebooks/pdfm_earth_engine.ipynb)\* | Illustrates how Earth Engine data, such as nighttime lights, can also be predicted from the embeddings, enhancing geospatial understanding for environmental and socioeconomic forecasting. |
| [Prediction using global embeddings](https://colab.research.google.com/github/google-research/population-dynamics/blob/master/notebooks/pdfm_global_embeddings_example.ipynb)\* | Illustrates the usage of global embeddings by setting up a multi-country model to predict for a new country. |

\* This notebook uses ZIP code embeddings and needs to be updated to S2 cells.

## Related resources

To explore peer-reviewed research and real-world validations of Population
Dynamics Insights, see [Academic
research](https://developers.google.com/maps/documentation/population-dynamics-insights/academic-research).