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Data Analytics of Time Series

Data Analytics of Time Series

          
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About the Book

Welcome to "Data Analytics of Time Series," your comprehensive guide to understanding and harnessing the power of time series data in the realm of data analytics. Time series data, characterized by observations collected sequentially over time, is ubiquitous in diverse fields such as finance, healthcare, retail, manufacturing, and beyond. From stock prices and weather patterns to patient admissions and sensor readings, time series data provides invaluable insights into past trends, present dynamics, and future forecasts.

In this book, we embark on a journey to explore the principles, methodologies, and applications of data analytics specifically tailored for time series data. Whether you're a seasoned data scientist, a curious researcher, or an industry professional seeking to leverage time series data for actionable insights, this book serves as your roadmap to mastering the intricacies of time series analysis.

**What You'll Learn: **

1. **Fundamentals of Time Series Data: ** We'll start by delving into the fundamentals of time series data, including its characteristics, components, and challenges. You'll gain a deep understanding of how time series data differs from other types of data and how to effectively preprocess and visualize time series data.

2. **Time Series Modeling Techniques: ** Armed with the foundational knowledge of time series data, we'll explore a plethora of modeling techniques, ranging from traditional statistical methods like ARIMA (AutoRegressive Integrated Moving Average) and exponential smoothing to cutting-edge machine learning algorithms such as deep learning and ensemble methods.

3. **Forecasting and Prediction: ** Prediction lies at the heart of time series analytics. We'll delve into the art and science of time series forecasting, uncovering techniques for predicting future trends, detecting anomalies, and quantifying uncertainty. You'll learn how to build robust forecasting models that capture the inherent patterns and dynamics of time series data.

4. **Applications Across Industries: ** Time series analytics finds applications across a wide array of industries and domains. Through real-world case studies and examples, we'll showcase how time series analysis is applied in finance, healthcare, retail, energy, transportation, and more. From demand forecasting and anomaly detection to predictive maintenance and risk management, you'll discover the myriad ways in which time series analytics drives innovation and informs decision-making.

5. **Ethical Considerations and Privacy Concerns: ** As data practitioners, it's imperative to navigate the ethical considerations and privacy concerns inherent in working with time series data. We'll discuss the ethical implications of data analytics, including data privacy, fairness, transparency, and accountability, and provide guidance on how to uphold ethical principles in your data analytics endeavors.

**Who This Book Is For: **

This book is designed for data scientists, analysts, researchers, and industry professionals who seek to harness the power of time series data for actionable insights and informed decision-making. Whether you're a novice exploring the world of time series analytics or a seasoned practitioner looking to expand your toolkit, this book equips you with the knowledge, tools, and techniques to excel in the field of data analytics of time series.

Join us on this enlightening journey as we unravel the mysteries of time series data and unlock the transformative potential of data analytics. Let's embark on this adventure together, where data meets time and insight meets action.


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Product Details
  • ISBN-13: 9798324556402
  • Publisher: Amazon Digital Services LLC - Kdp
  • Publisher Imprint: Independently Published
  • Height: 229 mm
  • No of Pages: 160
  • Spine Width: 9 mm
  • Width: 152 mm
  • ISBN-10: 8324556400
  • Publisher Date: 01 May 2024
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Weight: 227 gr

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