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You're reading from  Natural Language Processing and Computational Linguistics

Product typeBook
Published inJun 2018
Reading LevelBeginner
PublisherPackt
ISBN-139781788838535
Edition1st Edition
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Bhargav Srinivasa-Desikan
Bhargav Srinivasa-Desikan
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Bhargav Srinivasa-Desikan

Bhargav Srinivasa-Desikan is a research engineer working for INRIA in Lille, France. He is a part of the MODAL (Models of Data Analysis and Learning) team, and he works on metric learning, predictor aggregation, and data visualization. He is a regular contributor to the Python open source community, and completed Google Summer of Code in 2016 with Gensim where he implemented Dynamic Topic Models. He is a regular speaker at PyCons and PyDatas across Europe and Asia, and conducts tutorials on text analysis using Python.
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Summary


This brings us to the end of our chapter on spaCy and dependency parsing. The previous four chapters have illustrated the many powers of spaCy, and how we can harness these powers. Dependency parsing, in particular, remains very important to us as finding semantic or syntactic relationships between words within sentences can have many uses, whether it is simply identifying the most used adjectives or adverbs for a particular word or mapping custom relationships.

In the next chapters, we will move on from computational linguistics-based algorithms to information retrieval-based algorithms to conduct our text analysis. In particular, this will be topic models as well as clustering and classification algorithms.

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Natural Language Processing and Computational Linguistics
Published in: Jun 2018Publisher: PacktISBN-13: 9781788838535

Author (1)

author image
Bhargav Srinivasa-Desikan

Bhargav Srinivasa-Desikan is a research engineer working for INRIA in Lille, France. He is a part of the MODAL (Models of Data Analysis and Learning) team, and he works on metric learning, predictor aggregation, and data visualization. He is a regular contributor to the Python open source community, and completed Google Summer of Code in 2016 with Gensim where he implemented Dynamic Topic Models. He is a regular speaker at PyCons and PyDatas across Europe and Asia, and conducts tutorials on text analysis using Python.
Read more about Bhargav Srinivasa-Desikan