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Advanced Forecasting with Python: With State-Of-The-Art-Models Including Lstms, Facebook`s Prophet, and Amazon`s Deepar, Korstanje Joos


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Автор: Korstanje Joos
Название:  Advanced Forecasting with Python: With State-Of-The-Art-Models Including Lstms, Facebook`s Prophet, and Amazon`s Deepar
ISBN: 9781484271490
Издательство: Springer
Классификация:

ISBN-10: 1484271491
Обложка/Формат: Paperback
Страницы: 296
Вес: 0.60 кг.
Дата издания: 17.08.2021
Язык: English
Издание: 1st ed.
Иллюстрации: 36 illustrations, color; 70 illustrations, black and white; xvii, 296 p. 106 illus., 36 illus. in color.
Размер: 25.40 x 17.78 x 1.68 cm
Читательская аудитория: Professional & vocational
Подзаголовок: With state-of-the-art-models including lstms, facebook`s prophet, and amazon`s deepar
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: PART I: Machine Learning for Forecasting
Chapter 1: Models for ForecastingChapter Goal: Explains the different categories of models that are relevant for forecasting in high level languageNo pages: 10Sub -Topics1. Time series models2. Supervised vs unsupervised models3. Classification vs regression models4. Univariate vs multivariate models
Chapter 2: Model Evaluation for ForecastingChapter Goal: Explains model evaluation with specific adaptations to keep in mind for forecastingNo pages: 15Sub -Topics1. Train test split2. Cross validation for forecasting3. Backtesting
PART II: Univariate Time Series Models
Chapter 3: The AR ModelChapter Goal: explain the AR model (intuitively, mathematically and give python application with code and data set)No pages: 8Sub -Topics1. Understanding AR model2. Mathematical explanation of the AR model3. Worked out Python forecasting example with the AR model
Chapter 4: The MA modelChapter Goal: explain the MA model (intuitively, mathematically and give python application with code and data set)No pages: 8Sub -Topics1. Understanding MA model2. Mathematical explanation of the MA model3. Worked out Python forecasting example with the MA model
Chapter 5: The ARMA modelChapter Goal: explain the ARMA model (intuitively, mathematically and give python application with code and data set)No pages: 8Sub -Topics1. Understanding ARMA model2. Mathematical explanation of the ARMA model3. Worked out Python forecasting example with the ARMA model
Chapter 6: The ARIMA modelChapter Goal: Explains the ARIMA model (intuitively, mathematically and give python application with code and data set)No pages: 8Sub -Topics1. Understanding ARIMA model2. Mathematical explanation of the ARIMA model3. Worked out Python forecasting example with the ARIMA model
Chapter 7: The SARIMA ModelChapter Goal: Explains the SARIMA model (intuitively, mathematically and give python application with code and data set)No pages: 8Sub -Topics1. Understanding SARIMA model2. Mathematical explanation of the SARIMA model3. Worked out Python forecasting example with the SARIMA model
PART III: Multivariate Time Series Models
Chapter 8: The VAR modelChapter Goal: Explains the VAR model (intuitively, mathematically and give python application with code and data set)No pages: 8Sub -Topics1. Understanding VAR model2. Mathematical explanation of the VAR model3. Worked out Python forecasting example with the VAR model
Chapter 9: The Bayesian VAR modelChapter Goal: Explains the Bayesian VAR model (intuitively, mathematically and give python application with code and data set)No pages: 8Sub -Topics1. Understanding Bayesian VAR model2. Mathematical explanation of the Bayesian VAR model3. Worked out Python forecasting example with the Bayesian VAR model
PART IV: Supervised Machine Learning Models
Chapter 10: The Linear Regression modelChapter Goal: Explains the Linear Regression model (intuitively, mathematically and give python application with code and data set)No pages: 8Sub -Topics1. Understanding Linear Regression model



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