Assessing Product Quality or Direction for Spectral or Chromatographic Data

Are you responsible for making decisions about chemical processes or products based on large amounts of messy data? Is your data in multiple formats received from samples or from inline or offline laboratory equipment? Do you need to relate measurements made on a chemical system to a state or property of the system? Are you a chemical analyst on a team that needs to assure, improve or match the quality of consumer products or food products based on chemical attributes? Are you asked to make sense of and draw conclusions from spectra for mixtures?

In this session we use a case study for near-infrared transmission analysis of gluten and starch powder mixtures to show how to:

• Import multiple file types.
• Clean and pre-process the data interactively in a way that can be applied to new data.
• Explore the data to uncover possible patterns.
• Build, interpret, compare and select predictive models to meet your product or process goals.

Suggested prerequisites:

• Familiarity with spectral data inputs and responses.
• Some experience building predictive models.