£71.36

Springer Applied Time Series Analysis and Forecasting with Python (Statistics and Computing)

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Description

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, the book will equallyappeal to industry professionals in the fields of artificial intelligence and data science, and anyone interested in using Python to solve time series problems.

Key Features

Applied Time Series Analysis and Forecasting with Python

Books Subjects Computers Technology Programming Languages Python Books Subjects Business Money Education Reference Statistics Books Subjects Computers Technology Computer Science AI Machine Learning Intelligence Semantics Books Subjects Computers Technology General Books Subjects Science Math Mathematics Applied Statistics Books Subjects Computers Technology Software Mathematical Statistical Featured Stores Books Subjects Business Money Economics Econometrics

Product Type: ABIS BOOK

Springer

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
20 October 2022
Listed Since
02 July 2022

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No barcode data available

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