Machine Learning has become more and more popular. It's become accessible to a wider variety of users. And it is getting better and better at handling data - whether big or small. However one thing remains true about the data used in analysis - it is, most of the time, structured. Regardless of whether the data is stored in Excel spreadsheets, relational databases or big data repositories, it is structured. That is to say, it comes in the form of columns and rows of numbers, categories or labels.
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An interview with Dr. Bernardo Perez Orozco
Q. Bernardo your upcoming webinar is titled "Using NLP to unlock hidden meaning in the data you already have." What are you going to cover?
A. Historically, the information-value of free-text has mostly been out-of-reach for automated solutions. However, recent developments in Machine Learning – Natural Language Processing in particular – have made it increasingly possible to extract hidden treasures from free text via automation. This development resets some practical boundaries. I’ll show an example of how this works, using Mind Foundry’s Analyze platform and a set of news stories.