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Explore a comprehensive conference talk on the critical role of data annotation in Natural Language Processing (NLP). Delve into insights from Veronika Feherova, Director of Data Science, and Sima Sharifirad, Senior Data Scientist at Loblaw Companies Ltd. Learn about their experiences in building end-to-end data science solutions and applying machine learning algorithms across various industries. Discover how Loblaw's advanced analytics team streamlines the data annotation process to deliver high-quality training datasets for solving business problems in retail, health, and wellness. Gain valuable knowledge on approaches to ensure consistency and efficiency in data annotation for various NLP tasks, including tools to accelerate the process. Understand why creating good quality datasets is often the bottleneck in achieving high performance in NLP models, despite the increasing availability of advanced model architectures.
Syllabus
The Importance of Data Annotation for NLP
Taught by
Toronto Machine Learning Series (TMLS)