Time Series Feature Engineering
Simon Winston
This comprehensive guide is your key to unraveling the mysteries hidden within sequential data, whether you're navigating financial markets, predicting climate patterns, or optimizing business operations.
From seasoned data scientists to curious beginners, this book provides a rich exploration of time series feature engineering, demystifying the complexities of temporal data analysis. Dive into the intricacies of identifying trends, capturing seasonality, and decoding the hidden patterns that define time-varying phenomena. With practical examples, hands-on exercises, and real-world applications, you'll gain the skills to transform raw temporal data into actionable insights.
Discover the art of crafting meaningful features that empower your predictive models. Whether you're dealing with daily stock prices, hourly energy consumption, or monthly sales figures, "Temporal Insights" equips you with the knowledge to engineer features that resonate with the rhythm of your data.
"Time Series Feature Engineering" is your compass through the dynamic landscape of time series feature engineering. Whether you're aiming to forecast stock prices, predict customer demand, or optimize resource allocation, this book empowers you to harness the temporal dimension of data and extract meaningful insights that stand the test of time. Elevate your data science journey with the indispensable skills offered in " Time Series Feature Engineering: Unveiling Patterns and Trends through Time Series Feature Engineering."
Duration - 4h 15m.
Author - Simon Winston.
Narrator - Sam Finley.
Published Date - Saturday, 25 January 2025.
Copyright - © 2025 Simon Winston ©.
Location:
United States
Description:
This comprehensive guide is your key to unraveling the mysteries hidden within sequential data, whether you're navigating financial markets, predicting climate patterns, or optimizing business operations. From seasoned data scientists to curious beginners, this book provides a rich exploration of time series feature engineering, demystifying the complexities of temporal data analysis. Dive into the intricacies of identifying trends, capturing seasonality, and decoding the hidden patterns that define time-varying phenomena. With practical examples, hands-on exercises, and real-world applications, you'll gain the skills to transform raw temporal data into actionable insights. Discover the art of crafting meaningful features that empower your predictive models. Whether you're dealing with daily stock prices, hourly energy consumption, or monthly sales figures, "Temporal Insights" equips you with the knowledge to engineer features that resonate with the rhythm of your data. "Time Series Feature Engineering" is your compass through the dynamic landscape of time series feature engineering. Whether you're aiming to forecast stock prices, predict customer demand, or optimize resource allocation, this book empowers you to harness the temporal dimension of data and extract meaningful insights that stand the test of time. Elevate your data science journey with the indispensable skills offered in " Time Series Feature Engineering: Unveiling Patterns and Trends through Time Series Feature Engineering." Duration - 4h 15m. Author - Simon Winston. Narrator - Sam Finley. Published Date - Saturday, 25 January 2025. Copyright - © 2025 Simon Winston ©.
Language:
English
Opening Credits
Duration:00:00:13
Chapter 1 Introduction to time series feature engineering
Duration:00:06:48
Chapter 2 Fundamentals of time series data
Duration:00:32:21
Chapter 3 Preparing time series data for feature engineering
Duration:00:12:13
Chapter 4 Time based features
Duration:00:22:49
Chapter 5 Statistical features
Duration:00:18:26
Chapter 6 Frequency domain features
Duration:00:25:56
Chapter 7 Time series decomposition techniques
Duration:00:12:12
Chapter 8 Advanced techniques in feature engineering
Duration:00:22:40
Chapter 9 Feature scaling and normalization
Duration:00:20:36
Chapter 10 Case studies and applications
Duration:00:15:13
Chapter 11 Challenges and best practices
Duration:00:54:49
Chapter 12 Future trends in time series feature engineering
Duration:00:11:10
Ending Credits
Duration:00:00:14