Understanding Unstructured Data with Language Models – Alex Peattie
As data scientists, we’ve seen a rapid improvement in the last few decades in the tools available for working with structured data (be it tabular data, graph data, sensor data etc.). Yet, the vast majority of our data (Merrill Lynch puts the figure at roughly 90%) is *unstructured*, and lives in the form of documents, emails, reviews, reports, and chat logs etc. Many of us are far less familiar with how to analyze and understand this trove of unstructured data.
This talk focuses on language models, one of the most fundamental tools for working with unstructured data. The first part of the talk focuses on getting a thorough understanding of what a language model is, and how it works.
We then proceed to the present day, looking at how techniques like word vectors and transfer learning have yielded an improved generation of tools. In the second half of the talk, we look at how we can practically use language models to understand unstructured data.
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