Analyse Customer Data and Recommend Products with PixieDust
Details
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This hands on workshop is in collaboration with the Machine intelligence Garage at Digital Catapult
If you have always wanted to learn how to explore data with Python in charts, maps and even interactive dashboards or if you want to get more efficient with PixieDust then this hands-on workshop is for you!
In this meetup you will use data from a same-day grocery delivery service to:
- Explore and analyse customer behavior information (such as demographics and shopping cart values)
- Build a machine learning recommendation engine to encourage additional purchases based on past buying behavior
You will use Jupyter Notebooks with Python, Apache Spark and PixieDust, which you can run either on your own laptop or on Watson Studio. After building the recommendation model with Spark ML you will deploy it as an API with Watson Machine Learning that you can access from everywhere. The last thing to build is a PixieApp that uses this API in an interactive app in the notebook.
You will need:
- A laptop
You will learn about:
- Jupyter notebooks
- Python
- Apache Spark
- PixieDust
- Watson Studio
- Watson Machine Learning
Speaker: Margriet Groenendijk
Agenda:
18.30 - 19.00: Registration, Food, Drinks and Networking
19.00 - 19.15: Short Introduction of Jupyter notebooks and PixieDust
19.15 - 21.00: Hands on workshop