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Total Size:
41.8 MB
Info Hash:
EC0A432A206A833C33122C5898774C6E85D9CD61
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Added:
April 20, 2026, 8:05 a.m.
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(Last updated: April 20, 2026, 8:11 a.m.)
| File | Size |
|---|---|
| Ramaswami Y. Time Series Analysis with Spark. A practical guide...2025.pdf | 18.7 MB |
| Code.zip | 23.1 MB |
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212.4 MB
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2024-09-30
| Uploaded by kellyseamus | Size 212.4 MB | Health [ 5 /1 ] | Added 2024-09-30 |
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SOURCE: Ramaswami Y. Time Series Analysis with Spark. A practical guide...2025
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MEDIAINFO
Textbook in PDF format Master the fundamentals of time series analysis with Apache Spark and Databricks and uncover actionable insights at scale. Key Features Quickly get started with your first models and explore the potential of Generative AI. Learn how to use Apache Spark and Databricks for scalable time series solutions. Establish best practices to ensure success from development to production and beyond. Book Description Written 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 learn Understand the core concepts and architectures of Apache Spark. Clean and organize time series data. Choose the most suitable modeling approach for your use case. Gain expertise in building and training a variety of time series models. Explore ways to leverage Apache Spark and Databricks to scale your models. Deploy time series models in production. Integrate your time series solutions with big data tools for enhanced analytics. Leverage GenAI to enhance predictions and uncover patterns. Who this book is for If 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
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