Notebook narratives from industry: Inspirational real-world examples and reusable industry notebooks

Patty Ryan, Lee Stott, and Michael Lanzetta explore four industry examples of Jupyter notebooks that illustrate innovative applications of machine learning in manufacturing, retail, services, and education and share four reference industry Jupyter notebooks (available in both Python and R)along with demo datasetsfor practical application to your specific industry value areas.

Jupyter notebooks deliver a robust and flexible environment to simplify data analysis and collaboration across industry. Patty Ryan, Lee Stott, and Michael Lanzetta explore four industry examples of Jupyter notebooks that illustrate innovative applications of machine learning in manufacturing, retail, services, and education and share four reference industry Jupyter notebooks (available in both Python and R)—along with demo datasets—for practical application to your specific industry value areas. The examples are fully illustrated with data pipelines that highlight the preparation of classic data primitives ready for modeling and the actual modeling development. Each example includes a description of the customer journey from problem to approach, solution, and impact, along with Jupyter notebooks with synthetic datasets that allow you to replicate the application patterns. Patty, Lee, and Michael also share data primitive templates for each area, enabling pattern matching by helping you recognize or build the reference data within your organization or for your clients to apply these solutions. Topics include: