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  <titleInfo>
    <title>Machine Learning</title>
    <subTitle>for Time Series Forecasting With Python</subTitle>
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  <name type="personal">
    <namePart>Lazzeri, Francesca.</namePart>
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    <dateIssued encoding="marc">2020</dateIssued>
    <edition>1st ed.</edition>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>xxii,230 p.; PB 23.5 cm.</extent>
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  <tableOfContents>Machine Learning for Time Series Forecasting with Python is full real-world examples, resources, and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. This book is perfect for entry-level data scientists, business analysts, developers, and researchers. This book offers a comprehensive introduction to the core concepts, terminology, approaches, and applications of machine learning and deep learning for time series forecasting: understanding these principles leads to more flexible and successful time series applications.

Apart from this, in this Indian Adaptation, you’ll get:
·New self-evaluation Multiple Choice, Review, and Job-Interview Questions to equip the knowledge and confidence to excel in interviews
·India-specific case studies, Time Series Forecasting for Demand Planning at Flipkart and Predictive Maintenance at Tata Steel.
·Appendix on “Enhancing Time Series Forecasting for the Indian Market”</tableOfContents>
  <note type="statement of responsibility">Francesca Lazzeri.</note>
  <note>Machine Learning for Time Series Forecasting with Python is full real-world examples, resources, and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. This book is perfect for entry-level data scientists, business analysts, developers, and researchers. This book offers a comprehensive introduction to the core concepts, terminology, approaches, and applications of machine learning and deep learning for time series forecasting: understanding these principles leads to more flexible and successful time series applications.

Apart from this, in this Indian Adaptation, you’ll get:
·New self-evaluation Multiple Choice, Review, and Job-Interview Questions to equip the knowledge and confidence to excel in interviews
·India-specific case studies, Time Series Forecasting for Demand Planning at Flipkart and Predictive Maintenance at Tata Steel.
·Appendix on “Enhancing Time Series Forecasting for the Indian Market”</note>
  <subject>
    <topic>Time series data preparation</topic>
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  <subject>
    <topic/>
  </subject>
  <classification authority="ddc" edition="1">006.31 LAZF</classification>
  <identifier type="isbn">9789363866249</identifier>
  <identifier type="lccn">2020947403</identifier>
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