50 Shades of Text – Leveraging Natural Language Processing (NLP) to validate, improve, and expand the functionalities of a product
Nowadays, every company either stores or produces text data: from web logs and user queries, to translations and support tickets, yet not everyone knows how to extract valuable insights from it. In this session, we will present a practical case on how to move from raw text data to a valuable business application leveraging upon some of the major NLP methodologies (word embedding, word2vec, doc2vec, fastText, etc.)
Bio: Alessandro is a data veteran. He holds two Master’s degrees in computer engineering, one from Politecnico di Milano and the other from University of Illinois at Chicago (UIC).
He started his career in data consultancy, where he mastered Apache Spark for Machine Learning projects and subsequently joined WW Grainger, one of the largest MRO e-commerce companies in the United States. In September 2017, after more than 5 years in the USA, Alessandro returned to his native country, Italy, where he is now leading a team of data scientists. His current work focuses on achieving energy efficiency through the automation of energy management processes for commercial customers.
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