# Data Science Notebooks

Demand intelligence is a new and evolving field. We’ve created a number of Data Science Jupyter Notebooks to help you get started with PredictHQ’s intelligent event data. You’ll find guides to using our API with common Data Science tools, libraries in Python, and code samples.

<table data-card-size="large" data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Forecasts API Notebook</strong></td><td>Use our new Forecasts API to train a model in a few simple steps and focus on making use of the forecast results. Our API uses the same underlying XGBoost-based algorithm as the following notebook.</td><td><a href="/files/qapbKtZxFuPXFH6KeJvm">/files/qapbKtZxFuPXFH6KeJvm</a></td><td></td><td><a href="https://github.com/predicthq/phq-data-science-docs/blob/master/forecasts-api/demand_forecasting_with_phq_forecasts_api.ipynb">https://github.com/predicthq/phq-data-science-docs/blob/master/forecasts-api/demand_forecasting_with_phq_forecasts_api.ipynb</a></td></tr><tr><td><strong>Beam Notebooks</strong></td><td>Designed to provide you with the context you need to get started with the Beam API to find relevant events and use it effectively.</td><td><a href="/files/ZiHUXUhQV4UcLVmteaBj">/files/ZiHUXUhQV4UcLVmteaBj</a></td><td></td><td><a href="/pages/Gue0Nq6lLgbIaWCATKRw">/pages/Gue0Nq6lLgbIaWCATKRw</a></td></tr><tr><td><strong>Features API Notebook</strong></td><td>A how-to guide with details on how to retrieve machine learning features using Features API.</td><td><a href="/files/MSoXowQNtUJuRunoGuau">/files/MSoXowQNtUJuRunoGuau</a></td><td></td><td><a href="/pages/JHoYyfYNHkXBdP5y1UaD">/pages/JHoYyfYNHkXBdP5y1UaD</a></td></tr><tr><td><strong>Demand Forecasting Notebook</strong></td><td>Step-by-step guide on how to use PredictHQ event features in your existing demand forecasting models.</td><td><a href="/files/H4emh2xTl3AJ0f78ngym">/files/H4emh2xTl3AJ0f78ngym</a></td><td></td><td><a href="/pages/5wdf9fTc3lfbAIrVi9ZK">/pages/5wdf9fTc3lfbAIrVi9ZK</a></td></tr><tr><td><strong>Attendance-Based Events Notebooks</strong></td><td>Attended Events are scheduled to occur at a specific location and usually depend on attendance, such as conferences, expos, concerts, festivals, performing-arts, sports and community.</td><td><a href="/files/H9jrO1kxkXokOx0fCaaG">/files/H9jrO1kxkXokOx0fCaaG</a></td><td></td><td><a href="/pages/Pb3JPsAemm9MRBR8hTIC">/pages/Pb3JPsAemm9MRBR8hTIC</a></td></tr><tr><td><strong>Non-Attendance-Based Events Notebooks</strong></td><td>Non-Attendance-Based Events are events with a start and end date, but are more fluid and distributed in impact, such as observances or school holidays.</td><td><a href="/files/r5RA9bFa4w241GLO1TZr">/files/r5RA9bFa4w241GLO1TZr</a></td><td></td><td><a href="/pages/BUExzXpRh4sAIcMpdXJM">/pages/BUExzXpRh4sAIcMpdXJM</a></td></tr><tr><td><strong>Severe Weather Event Notebooks</strong></td><td>Severe weather is any dangerous meteorological phenomenon with the potential to cause damage, serious social disruption, or loss of human life.</td><td><a href="/files/I34A4myxZDqUv14T6N09">/files/I34A4myxZDqUv14T6N09</a></td><td></td><td><a href="/pages/6YT2c5aESF59QDIXcZd4">/pages/6YT2c5aESF59QDIXcZd4</a></td></tr><tr><td><strong>Academic Events Notebooks</strong></td><td>Academic Events are captured from an individual higher education institute’s academic calendar. They outline the general undergraduate activities, for example instruction period, break, exams, graduation, social, etc.</td><td><a href="/files/NjTp3S9DBxTYrkIlITT1">/files/NjTp3S9DBxTYrkIlITT1</a></td><td></td><td><a href="/pages/6nQnlpznMZpKYRZkRef6">/pages/6nQnlpznMZpKYRZkRef6</a></td></tr><tr><td><strong>Live TV Events Notebooks</strong></td><td>Live TV Events covers live broadcast sports games with a large number of people watching at a particular time across different counties across the United States.</td><td><a href="/files/SETkfZGFrUVNTJ8yk4B3">/files/SETkfZGFrUVNTJ8yk4B3</a></td><td></td><td><a href="/pages/0PdDLiIzew6PeuSoKzP8">/pages/0PdDLiIzew6PeuSoKzP8</a></td></tr><tr><td><strong>Working with Venues Notebook</strong></td><td>Guide to exploring PredictHQ’s venue information.</td><td><a href="/files/NPZNo47gAB6TE2hsVeyF">/files/NPZNo47gAB6TE2hsVeyF</a></td><td></td><td><a href="/pages/WU99fOMEenTo26v1nq1y">/pages/WU99fOMEenTo26v1nq1y</a></td></tr></tbody></table>

All our Data Science Notebooks can be found in our [GitHub repo](https://github.com/predicthq/phq-data-science-docs/tree/master).


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