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Modern Time Series Forecasting with Python - Modern Time Series Forecasting with Python - Second Edition (Packt Publishing, Manu Joseph)

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Author

Manu Joseph

Highlights

Binding: Packt Publishing
Publisher: Bookbaazi
Genre: Analyzing and Visualizing Time Series Data
ISBN: 9781835883181, 1835883184
Edition: 2nd, 2024
Pages: 658

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Specifications

Book Details

Publication Year	2024 October
Edition Type	31 October 2024
Book Type	professional software
Table of Contents	- Introducing Time Series - Acquiring and Processing Time Series Data - Analyzing and Visualizing Time Series Data - Setting a Strong Baseline Forecast - Time Series Forecasting as Regression - Feature Engineering for Time Series Forecasting - Target Transformations for Time Series Forecasting - Forecasting Time Series with Machine Learning Models - Ensembling and Stacking - Global Forecasting Models - Introduction to Deep Learning - Building Blocks of Deep Learning for Time Series - Common Modeling Patterns for Time Series - Attention and Transformers for Time Series
Net Quantity	1

Contributors

Author Info

Manu Joseph

School Books Details

Subject

professional software

University Books Details

Stream	professional software
Degree/Diploma	Degree
Specialization	professional software

Additional Features

Other Features

This book is ideal for data scientists, financial analysts, quantitative analysts, machine learning engineers, and researchers who need to model time-dependent data across industries, such as finance, energy, meteorology, risk analysis, and retail. Whether you are a professional looking to apply cutting-edge models to real-world problems or a student aiming to build a strong foundation in time series analysis and forecasting, this book will provide the tools and techniques you need. Familiarity with Python and basic machine learning concepts is recommended.

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