<?xml version="1.0" encoding="UTF-8"?>
<mods xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.loc.gov/mods/v3" version="3.1" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
  <titleInfo>
    <title>Applied text analysis with Python</title>
    <subTitle>enabling language-aware data products with machine learning</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Bengfort, Benjamin</namePart>
    <namePart type="date">1984-</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Bilbro, Rebecca</namePart>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Ojeda, Tony</namePart>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">cau</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Sebastopol, CA</placeTerm>
    </place>
    <publisher>O'Reilly Media, Inc.</publisher>
    <dateIssued>2018</dateIssued>
    <copyrightDate encoding="marc">2018</copyrightDate>
    <edition>First edition.</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>xviii, 310 pages : illustrations ; 25 cm</extent>
  </physicalDescription>
  <abstract>From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist's approach to building language-aware products with applied machine learning. You will learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you'll be equipped with practical methods to solve any number of complex real-world problems.- Preprocess and vectorize text into high-dimensional feature representations - Perform document classification and topic modeling - Steer the model selection process with visual diagnostics - Extract key phrases, named entities, and graph structures to reason about data in text - Build a dialog framework to enable chatbots and language-driven interaction - Use Spark to scale processing power and neural networks to scale model complexity.--</abstract>
  <tableOfContents>Language and computation -- Building a custom corpus -- Corpus preprocessing and wrangling -- Text vectorization and transformation pipelines -- Classification for text analysis -- Clustering for text similarity -- Context-aware text analysis -- Text visualization -- Graph analysis of text -- Chatbots -- Scaling text analytics with multiprocessing and Spark -- Deep learning and beyond.</tableOfContents>
  <targetAudience authority="marctarget">adult</targetAudience>
  <note type="statement of responsibility">Benjamin Bengfort, Rebecca Bilbro, and Tony Ojeda.</note>
  <note>Includes index.</note>
  <note>AAL</note>
  <subject authority="lcsh">
    <topic>Natural language processing (Computer science)</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Python (Computer program language)</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Machine learning</topic>
  </subject>
  <subject authority="">
    <topic>Machine learning</topic>
  </subject>
  <subject authority="">
    <topic>Natural language processing (Computer science)</topic>
  </subject>
  <subject authority="">
    <topic>Python (Computer program language)</topic>
  </subject>
  <classification authority="lcc">QA76.73.P98 B454 2018</classification>
  <classification authority="ddc" edition="23">006.35</classification>
  <identifier type="isbn">1491963042</identifier>
  <identifier type="isbn">9781491963043</identifier>
  <identifier type="lccn">2018276483</identifier>
  <location>
    <physicalLocation>Ayesha Abed Library</physicalLocation>
  </location>
  <recordInfo>
    <recordContentSource authority="marcorg">YDX</recordContentSource>
    <recordCreationDate encoding="marc">260621</recordCreationDate>
    <recordChangeDate encoding="iso8601">20260621160624.0</recordChangeDate>
    <recordIdentifier source="BD-DhAAL">45959</recordIdentifier>
    <languageOfCataloging>
      <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
    </languageOfCataloging>
  </recordInfo>
</mods>
