The book covers concepts, techniques, and algorithms commonly used and moreadvanced and recent approaches with practical use. For example, you will learn to trainand validate different models covering statistical methods, machine learning algorithms,and various deep learning architectures for forecasting and outlier (or anomaly) detection.Most importantly, the variety of datasets used in this book will give you a better insightinto how these different models work and how you can pick the most appropriateapproach to solve your specific problem.

Time Series Analysis with Python Cookbook - Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation PDF

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