Lecture 15 – Text summarization in Natural Language Processing
Extractive and abstractive text summarization techniques with examples and evaluation metrics like ROUGE. As the volume of digital […]
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Lecture 14 – Question answering in Natural Language Processing
How question answering systems work, from information retrieval based pipelines to modern neural approaches in Natural Language Processing. […]
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Lecture 13 – Machine Translation in Natural Language Processing. From Rule Based to Neural
How machine translation evolved from rule based and statistical methods to modern neural MT with attention. Automatic translation […]
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Lecture 12 – Information Extraction and Relation Extraction
Explore information extraction, named entity recognition and relation extraction using dependency and constituency grammars. Most text on the […]
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Lecture 11 – Information Retrieval, Vector Space Model and Evaluation
Understand information retrieval basics, vector space model, cosine similarity and evaluation using precision and recall. Search is one […]
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Lecture 10 – Text Classification with Bag-of-Words and TF-IDF in NLP
Text classification is one of the most practical skills in Natural Language Processing. Whenever we automatically categorise emails […]
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