Time Series Data Analysis
Brian Paul
From the fundamentals of time series components to the complexities of modern forecasting models, the book navigates through the nuances of stationarity, seasonality, and autocorrelation, equipping readers with the tools to identify and leverage patterns within time-dependent data. Through detailed exploration of data preparation, exploratory data analysis, and a variety of forecasting methods, from classical approaches like ARIMA to cutting-edge deep learning techniques, this book lays a solid foundation for predictive modeling.
Key Features:
In-depth Coverage:Practical Case Studies:Cutting-edge Techniques:Evaluation Strategies:Tools and Software:Time Series Data Analysis: A Comprehensive Guide for Very Beginner is your key to unlocking the predictive power of time-dependent data. Embrace the opportunity to transform raw data into insightful forecasts that can drive decision-making and innovation in any field.
Duration - 7h 56m.
Author - Brian Paul.
Narrator - Ray Collins.
Published Date - Thursday, 22 January 2026.
Copyright - © 2025 Khin Soe ©.
Location:
United States
Description:
From the fundamentals of time series components to the complexities of modern forecasting models, the book navigates through the nuances of stationarity, seasonality, and autocorrelation, equipping readers with the tools to identify and leverage patterns within time-dependent data. Through detailed exploration of data preparation, exploratory data analysis, and a variety of forecasting methods, from classical approaches like ARIMA to cutting-edge deep learning techniques, this book lays a solid foundation for predictive modeling. Key Features: In-depth Coverage:Practical Case Studies:Cutting-edge Techniques:Evaluation Strategies:Tools and Software:Time Series Data Analysis: A Comprehensive Guide for Very Beginner is your key to unlocking the predictive power of time-dependent data. Embrace the opportunity to transform raw data into insightful forecasts that can drive decision-making and innovation in any field. Duration - 7h 56m. Author - Brian Paul. Narrator - Ray Collins. Published Date - Thursday, 22 January 2026. Copyright - © 2025 Khin Soe ©.
Language:
English
Opening Credits
Duration:00:00:07
Introduction to time series analysis
Duration:00:10:50
Fundamental concepts in time series
Duration:00:31:03
Data preparation and cleaning for time
Duration:00:23:29
Exploratory data analysis (eda) for time
Duration:00:31:40
Time series forecasting methods
Duration:00:11:02
Machine learning in time series analysis
Duration:00:12:47
Deep learning for time series forecasting
Duration:00:16:59
Evaluating forecasting models
Duration:00:28:36
Case studies and applications
Duration:00:15:34
Advanced topics in time series analysis
Duration:00:17:42
Tools and software for time series
Duration:00:12:42
Best practices and pitfalls in time
Duration:00:14:23
Future directions in time series analysis
Duration:00:30:53
Opening credits
Duration:00:00:14
Getting started with r
Duration:00:40:01
Time series data in r
Duration:00:16:10
Time series decomposition
Duration:00:27:54
Autoregressive integrated moving average
Duration:00:14:14
Seasonal arima and sarima models
Duration:00:12:24
Advanced time series models
Duration:00:15:59
Time series cross validation
Duration:00:08:47
Case studies
Duration:00:13:46
Best practices and tips for time series
Duration:00:48:52
Ending Credits
Duration:00:00:07