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.
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Patty Ryan leads prototyping engagements with partners, both large and small, on the Technology Evangelism and Development team at Microsoft. She specializes in designing and operationalizing predictive models that inform strategies, focus customer outreach, and increase engagement. Previously, Patty led telemetry, analytics, UX, and support in Dynamics, Azure Identity, and O365, driving innovation in customer-facing self-service and distributed analytics.
Lee Stott is CTO of academic engagements at Microsoft, where he engages academic institutions across the UK in the ongoing development of the Microsoft platform. Lee has held a number of roles at Microsoft, including academic and technical evangelist. Previously, Lee was the head of information systems at the University of Manchester, where he led service and delivery teams across both academic and commercial markets. Lee holds a PGCE in higher education management from the University of Southampton and an MSc in information technology from the University of Liverpool.
Michael Lanzetta is a principal SDE at Microsoft. In his more than 20-year career in the software industry, he’s worked in domains as varied as circuit design and drug discovery and in languages from JavaScript to F#, but his primary focus has always been scaled-out server-side work. Michael has a background in demand forecasting from Manugistics and Amazon and machine learning from Bing; he has spent the last few years building intelligent services on Azure using everything from Spark to TensorFlow and CNTK.
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