Advanced NLP - Experimental Design and Data Annotation - Lecture 9
Graham Neubig via YouTube
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Overview
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Explore experimental design and data annotation techniques in this lecture from CMU's Advanced Natural Language Processing course. Delve into crucial aspects of NLP research methodology, including how to design effective experiments and properly annotate data for machine learning tasks. Learn best practices for creating robust datasets, avoiding common pitfalls in experimental setups, and ensuring the quality and reliability of annotated data. Gain insights into the importance of these foundational skills for conducting rigorous NLP research and developing high-performance language models.
Syllabus
CMU Advanced NLP Fall 2024 (9): Experimental Design and Data Annotation
Taught by
Graham Neubig
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I learnt the foundational background of experimental design which start from observation to research topic to forming hypotheses to testing hypothesis with experiments then analyzing the data obtained before proceeding to writing your report
Finding a research topic area is made easy using keywords such as find older/new papers
Read abstract and introduction read details of most relevant papers make a short summary I leant automation workflow and computational resources websites such as Amazon web services and google cloud