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You're reading from  Distributed Data Systems with Azure Databricks

Product typeBook
Published inMay 2021
Reading LevelBeginner
PublisherPackt
ISBN-139781838647216
Edition1st Edition
Languages
Python
Tools
Azure Functions
Concepts
Data Science
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Author (1)
Alan Bernardo Palacio
Alan Bernardo Palacio
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Alan Bernardo Palacio

Alan Bernardo Palacio is a data scientist and an engineer with vast experience in different engineering fields. His focus has been the development and application of state-of-the-art data products and algorithms in several industries. He has worked for companies such as Ernst and Young, Globant, and now holds a data engineer position at Ebiquity Media helping the company to create a scalable data pipeline. Alan graduated with a Mechanical Engineering degree from the National University of Tucuman in 2015, participated as the founder in startups, and later on earned a Master's degree from the faculty of Mathematics in the Autonomous University of Barcelona in 2017. Originally from Argentina, he now works and resides in the Netherlands.
Read more about Alan Bernardo Palacio

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Extracting features from text

Extracting information from text relies on being able to capture the underlying language structure. This means that we intend to capture the meaning and relationship among tokens and the meaning they try to convey within a sentence. These sorts of manipulations and tasks associated with understanding the meaning in text yield a whole branch of an interdisciplinary field called natural language processing (NLP). Here, we will focus on some examples related to transforming text into numerical features that can be used later on the machine learning and deep learning algorithms using the PySpark API in Azure Databricks.

TF-IDF

Term Frequency-Inverse Document Frequency (TF-IDF) is a very commonly used text preprocessing operation to convert sentences into features created based on the relative frequency of the tokens that compose them. The term frequency-inverse is used to create a set of numerical features that are constructed based on how relevant...

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Distributed Data Systems with Azure Databricks
Published in: May 2021Publisher: PacktISBN-13: 9781838647216
© 2021 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Alan Bernardo Palacio

Alan Bernardo Palacio is a data scientist and an engineer with vast experience in different engineering fields. His focus has been the development and application of state-of-the-art data products and algorithms in several industries. He has worked for companies such as Ernst and Young, Globant, and now holds a data engineer position at Ebiquity Media helping the company to create a scalable data pipeline. Alan graduated with a Mechanical Engineering degree from the National University of Tucuman in 2015, participated as the founder in startups, and later on earned a Master's degree from the faculty of Mathematics in the Autonomous University of Barcelona in 2017. Originally from Argentina, he now works and resides in the Netherlands.
Read more about Alan Bernardo Palacio

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