Time Series Books

Name	Cost	Author (Year)	Description
Time Series Analysis Handbook	Free	PhDs at Asian Institute of Management (2023)	This handbook extensively covers time series analysis and forecasting, delving from the most fundamental methods to the state-of-the-art. The handbook was made in Python and is designed such that readers can both learn the theory and apply them to real-world problems.
Forecasting: Principles and Practice (3rd ed)	Free	Rob J Hyndman and George Athanasopoulos (2021)	This textbook is intended to provide a comprehensive introduction to forecasting methods and to present enough information about each method for readers to be able to use them sensibly.
Time Series Analysis with Python Cookbook	Paid	Tarek A. Atwan (2022)	Explore forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms.
Modern Time Series Forecasting with Python	Paid	Manu Joseph (2022)	Build real-world time series forecasting systems which scale to millions of time series by applying modern machine learning and deep learning concepts.
Time Series Forecasting in Python	Paid	Marco Peixeiro (2022)	Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting.
Hands-On Time Series Analysis with R	Paid	Rami Krispin (2019)	Build efficient forecasting models using traditional time series models and machine learning algorithms using R.
Forecasting Time Series Data with Prophet	Paid	Greg Rafferty (2023)	Create and improve fully automated forecasts for time series data with strong seasonal effects, holidays, and additional regressors using Prophet.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow	Paid	Aurélien Géron (2019)	This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.