Challenges and Analysis Examples in Time Series Data Analysis: A Specialized Book

★This will explain various analysis methods and practical challenges, introducing examples of analysis by application, from the collection and preprocessing of time series data to each analysis technique.

★An explanation of analytical methods that incorporate practical applications while capturing the characteristics of time series data by a total of 25 authors. 〇 What if the data behavior is too granular? How to group multiple datasets? etc. 〇 Causal exploration, state space models, etc... Addressing common practical challenges with each analytical method. 〇 Demand forecasting for sales and product prices, anomaly detection from normal data only, analysis by segmenting time series data, etc. Numerous case studies using real data are explained! What are the necessary data types, and what are the points for interpreting analysis results and improving accuracy? 〇 Measures to counter performance degradation during system operation, activities that should be carried out at each stage for AI evaluation, testing techniques, and quality assurance.

Technical and Reference Books