Interpreting and generating language is a crucial underpinning of any artificial intelligence (AI) project, and the application of deep learning approaches, such as natural language processing (NLP), has enabled many breakthroughs. However, to accomplish this, the complexity of some NLP tasks requires building a custom AI solution—among the most challenging projects within the data science discipline.
Antonio Fragoso explores the key aspects of implementing a natural language processing project within your organization and reveals the necessary steps for making it a success. Antonio focuses on how to leverage an iterative process that can pave the way toward building a successful product.
This session is sponsored by Globant.
Antonio Fragoso is a senior data scientist and technical leader at Globant, where he works with top-retail and financial services clients within Globant’s Artificial Intelligence and Big Data Studios. Antonio is responsible for helping clients revamp their analytics cycles and business operations through machine learning and deep learning initiatives.
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