From Modelling to Deep Learning: Advanced image
and text analysis

Do you collect image and/or unstructured text data as part of your research, development, or production activities? Are you finding manual analysis of such unstructured data to be difficult, tedious, or error-prone?

You’ve spent valuable time and effort collecting your data sets, and now want to put them to constructive use. You are therefore interested in reliably recognizing patterns from your images or text responsible for these defects – and doing so in a timely manner.

In this webinar, we introduce some novel ways to analyze image and text data to aid in classifying, predicting, and improving performance using deep learning methods that are simple to apply and master. The machine learning and modeling techniques within JMP Pro are powerful for analyzing tabular or spreadsheet data common in R&D and manufacturing.  A new add-in for use with JMP Pro allows users to extend this functionality to Deep Learning and AI models capable of image and text analysis. Using case studies, you can transform your data into meaningful insights, thus achieving better outcomes.

Case studies include:

• Predicting molecular properties from SMILES strings.
• Predicting defects from wafer map images.
• Predicting sentiment from product reviews.
• Predicting relevance from scientific titles and abstracts.

This webinar will be of interest to anyone working in research, development, or production who is collecting and wishing to make better use of unstructured data.

You will gain an understanding of what is possible with modern and easy to apply deep learning methods to aid richer understanding and better decisions from your unstructured data.