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Using a predictive analytics model to foresee flight delays

This paper describes how data scientists and developers can build an application to predict flight delays using a Get-Build-Analyze methodology and IBM® Analytics for Apache Spark , a managed Apache Spark service, with interactive Jupyter Notebooks. The application uses machine learning (Spark MLlib), fueled by publicly available airplane flight data and enriched with weather data, to predict flight delays due to weather conditions. In the event that a delay is likely, the app can also help determine the degree to which the flight will be delayed.

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Blue DME

Blue DME is an Artificial Intelligence Independent Software Vendor specialized in sales performance acceleration, external data discovery and data science that works in the insurance, banking, automotive and industry sectors. We created a SaaS platform that improves sales and marketing performance of companies with a complex sales cycle. It is based on predictive marketing technologies to anticipate the likely behaviour of a visitor / prospect / customer: we optimize the targeting of commercial actions (best offer for specific consumers most likely to be receptive at a given time). Operational insights & recommendations are then provided in real-time to the sales teams (prescriptive analytics).

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