Description: Applied Time Series Analysis and Forecasting With Python, Paperback by Huang, Changquan; Petukhina, Alla, ISBN 3031135865, ISBN-13 9783031135866, Like New Used, Free shipping in the US This textbook presents methods and techniques for time series analysis and forecasting and shows how to use Python to implement them and solve data science problems. It covers not only common statistical approaches and time series models, including ARMA, SARIMA, VAR, GARCH and state space and Markov switching models for (non)stationary, multivariate and financial time series, but also modern machine learning procedures and challenges for time series forecasting. Providing an organic combination of the principles of time series analysis and Python programming, it enables the reader to study methods and techniques and practice writing and running Python code at the same time. Its data-driven approach to analyzing and modeling time series data helps new learners to visualize and interpret both the raw data and its computed results. Primarily intended for students of statistics, economics and data science with an undergraduate knowledge of probability and statistics, th will equally appeal to industry professionals in the fields of artificial intelligence and data science, and anyone interested in using Python to solve time series problems.
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Book Title: Applied Time Series Analysis and Forecasting With Python
Number of Pages: X, 372 Pages
Publication Name: Applied Time Series Analysis and Forecasting with Python
Language: English
Publisher: Springer International Publishing A&G
Publication Year: 2023
Subject: Mathematical & Statistical Software, Probability & Statistics / General, General, Econometrics
Type: Textbook
Item Weight: 20.7 Oz
Author: Changquan Huang, Alla Petukhina
Item Length: 9.3 in
Subject Area: Mathematics, Computers, Business & Economics
Series: Statistics and Computing Ser.
Item Width: 6.1 in
Format: Trade Paperback
