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Margriet Groenendijk edited this page Aug 1, 2018 · 4 revisions

Short Name

Analyse historical shopping data with Spark and PixieDust in a Jupyter notebook

Short Description

Use Jupyter Notebooks with IBM Watson Studio to analyse historical shopping data. Using the open-source PixieDust Python package

build an interactive recommendation engine PixieApp. With Watson Machine Learning a clustering model is deployed and ready to be used as an API, which is explored and tested in a notebook and used in the interactive PixieApp.

Offering Type

Cognitive

Introduction

This code pattern shows how to ...

Author

By Patrick Titzler and Margriet Groenendijk

Code

Demo

  • link to demo video

Video

  • link to youtube video

Overview

In this code pattern historical shopping data is used to ...

When the reader has completed this code pattern, they will understand how to:

Flow

  1. Log in to IBM Watson Studio
  2. Load the provided notebook into Watson Studio
  3. Load the customer data in the notebook
  4. Transform the data with Apacke Spark
  5. Create charts and maps with PixieDust

Included components

  • IBM Watson Studio: a suite of tools and a collaborative environment for data scientists, developers and domain experts
  • IBM Apache Spark: an open source cluster computing framework optimized for extremely fast and large scale data processing

Featured Technologies

  • Jupyter notebooks: an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text
  • PixieDust: Open source Python package, providing support for Javascript/Node.js code.

Blog

Blog Title: ***

Blog Author: Margriet Groenendijk

Blog Content - see below

Learn more

  • Watson Studio: Master the art of data science with IBM's Watson Studio
  • Data Analytics Code Patterns: Enjoyed this Code Pattern? Check out our other Data Analytics Code Patterns
  • With Watson: Want to take your Watson app to the next level? Looking to utilize Watson Brand assets? Join the With Watson program to leverage exclusive brand, marketing, and tech resources to amplify and accelerate your Watson embedded commercial solution.
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