AutoML for Natural Language Processing - EACL 2013 Tutorial
Offered By: Center for Language & Speech Processing(CLSP), JHU via YouTube
Course Description
Overview
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore automated machine learning (AutoML) techniques for natural language processing in this comprehensive EACL'13 tutorial. Delve into the emerging field of AutoML and its potential impact on NLP model building. Learn about hyperparameter optimization, neural architecture search, and other key topics that have gained prominence at major conferences like NeurIPS, ICML, and ICLR. Discover how automation can introduce rigor to the often ad hoc process of model development, moving beyond borrowing default hyperparameters and trying variant architectures. Gain insights into applying AutoML techniques to enhance the NLP model-building process, ensuring more optimal and rigorous results. This 2-hour and 44-minute tutorial, presented by Kevin Duh and Xuan Zhang from the Center for Language & Speech Processing (CLSP) at Johns Hopkins University, offers a thorough overview of AutoML methods and their practical applications in the field of natural language processing.
Syllabus
AutoML for Natural Language Processing - EACL'13 Tutorial - Kevin Duh, Xuan Zhang
Taught by
Center for Language & Speech Processing(CLSP), JHU
Related Courses
Building a unique NLP project: 1984 book vs 1984 albumCoursera Project Network via Coursera Exam Prep AI-102: Microsoft Azure AI Engineer Associate
Whizlabs via Coursera Amazon Echo Reviews Sentiment Analysis Using NLP
Coursera Project Network via Coursera Amazon Translate: Translate documents with batch translation
Coursera Project Network via Coursera Analyze Text Data with Yellowbrick
Coursera Project Network via Coursera