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Time Series Analysis with Spark

- A practical guide to processing, modeling, and forecasting time series with Apache Spark
Af: Yoni Ramaswami Engelsk Paperback

Time Series Analysis with Spark

- A practical guide to processing, modeling, and forecasting time series with Apache Spark
Af: Yoni Ramaswami Engelsk Paperback
Tjek vores konkurrenters priser
Master the fundamentals of time series analysis with Apache Spark and Databricks and uncover actionable insights at scaleKey FeaturesQuickly get started with your first models and explore the potential of Generative AILearn how to use Apache Spark and Databricks for scalable time series solutionsEstablish best practices to ensure success from development to production and beyondPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionWritten by Databricks Senior Solutions Architect Yoni Ramaswami, whose expertise in Data and AI has shaped innovative digital transformations across industries, this comprehensive guide bridges foundational concepts of time series analysis with the Spark framework and Databricks, preparing you to tackle real-world challenges with confidence. From preparing and processing large-scale time series datasets to building reliable models, this book offers practical techniques that scale effortlessly for big data environments. You’ll explore advanced topics such as scaling your analyses, deploying time series models into production, Generative AI, and leveraging Spark's latest features for cutting-edge applications across industries. Packed with hands-on examples and industry-relevant use cases, this guide is perfect for data engineers, ML engineers, data scientists, and analysts looking to enhance their expertise in handling large-scale time series data. By the end of this book, you’ll have mastered the skills to design and deploy robust, scalable time series models tailored to your unique project needs—qualifying you to excel in the rapidly evolving world of big data analytics.What you will learnUnderstand the core concepts and architectures of Apache SparkClean and organize time series dataChoose the most suitable modeling approach for your use caseGain expertise in building and training a variety of time series modelsExplore ways to leverage Apache Spark and Databricks to scale your modelsDeploy time series models in productionIntegrate your time series solutions with big data tools for enhanced analyticsLeverage GenAI to enhance predictions and uncover patternsWho this book is forIf you are a data engineer, ML engineer, data scientist, or analyst looking to enhance your skills in time series analysis with Apache Spark and Databricks, this book is for you. Whether you’re new to time series or an experienced practitioner, this guide provides valuable insights and techniques to improve your data processing capabilities. A basic understanding of Apache Spark is helpful, but no prior experience with time series analysis is required.
Tjek vores konkurrenters priser
Normalpris
kr 427
Fragt: 39 kr
6 - 8 hverdage
20 kr
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God 4 anmeldelser på
Tjek vores konkurrenters priser
Master the fundamentals of time series analysis with Apache Spark and Databricks and uncover actionable insights at scaleKey FeaturesQuickly get started with your first models and explore the potential of Generative AILearn how to use Apache Spark and Databricks for scalable time series solutionsEstablish best practices to ensure success from development to production and beyondPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionWritten by Databricks Senior Solutions Architect Yoni Ramaswami, whose expertise in Data and AI has shaped innovative digital transformations across industries, this comprehensive guide bridges foundational concepts of time series analysis with the Spark framework and Databricks, preparing you to tackle real-world challenges with confidence. From preparing and processing large-scale time series datasets to building reliable models, this book offers practical techniques that scale effortlessly for big data environments. You’ll explore advanced topics such as scaling your analyses, deploying time series models into production, Generative AI, and leveraging Spark's latest features for cutting-edge applications across industries. Packed with hands-on examples and industry-relevant use cases, this guide is perfect for data engineers, ML engineers, data scientists, and analysts looking to enhance their expertise in handling large-scale time series data. By the end of this book, you’ll have mastered the skills to design and deploy robust, scalable time series models tailored to your unique project needs—qualifying you to excel in the rapidly evolving world of big data analytics.What you will learnUnderstand the core concepts and architectures of Apache SparkClean and organize time series dataChoose the most suitable modeling approach for your use caseGain expertise in building and training a variety of time series modelsExplore ways to leverage Apache Spark and Databricks to scale your modelsDeploy time series models in productionIntegrate your time series solutions with big data tools for enhanced analyticsLeverage GenAI to enhance predictions and uncover patternsWho this book is forIf you are a data engineer, ML engineer, data scientist, or analyst looking to enhance your skills in time series analysis with Apache Spark and Databricks, this book is for you. Whether you’re new to time series or an experienced practitioner, this guide provides valuable insights and techniques to improve your data processing capabilities. A basic understanding of Apache Spark is helpful, but no prior experience with time series analysis is required.
Produktdetaljer
Sprog: Engelsk
Sider: 298
ISBN-13: 9781803232256
Indbinding: Paperback
Udgave:
ISBN-10: 1803232250
Udg. Dato: 28 mar 2025
Længde: 18mm
Bredde: 189mm
Højde: 234mm
Forlag: Packt Publishing Limited
Oplagsdato: 28 mar 2025
Forfatter(e): Yoni Ramaswami
Forfatter(e) Yoni Ramaswami


Kategori Informationsarkitektur


ISBN-13 9781803232256


Sprog Engelsk


Indbinding Paperback


Sider 298


Udgave


Længde 18mm


Bredde 189mm


Højde 234mm


Udg. Dato 28 mar 2025


Oplagsdato 28 mar 2025


Forlag Packt Publishing Limited

Kategori sammenhænge