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Modern Time Series Forecasting with Python: Explore industry-ready time series forecasting using modern machine learning and deep learning Cover

Modern Time Series Forecasting with Python: Explore industry-ready time series forecasting using modern machine learning and deep learning

Paid access
|Dec 2022
Table of contents

Table of Contents

  1. Introducing Time Series
  2. Acquiring and Processing Time Series Data
  3. Analyzing and Visualizing Time Series Data
  4. Setting a Strong Baseline Forecast
  5. Time Series Forecasting as Regression
  6. Feature Engineering for Time Series Forecasting
  7. Target Transformations for Time Series Forecasting
  8. Forecasting Time Series with Machine Learning Models
  9. Ensembling and Stacking
  10. Global Forecasting Models
  11. Introduction to Deep Learning
  12. Building Blocks of Deep Learning for Time Series
  13. Common Modeling Patterns for Time Series
  14. Attention and Transformers for Time Series
  15. Strategies for Global Deep Learning Forecasting Models
  16. Specialized Deep Learning Architectures for Forecasting
  17. Multi-Step Forecasting
  18. Evaluating Forecasts – Forecast Metrics
  19. Evaluating Forecasts – Validation Strategies

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PDF ISBN: 978-1-80323-204-1
Publisher: Packt Publishing Limited
Copyright owner: © 2022 Packt Publishing Limited
Publication date: 2022
Language: English
Pages: 552
Modern Time Series Forecasting with Python