Joseph Modern Time Series Forecasting with Python

Explore industry-ready time series forecasting using modern machine learning and deep learning
1. Auflage 2022
ISBN: 978-1-80323-204-1
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 552 Seiten

No detailed description available for "Modern Time Series Forecasting with Python".

Autoren/Hrsg.

Joseph, Manu

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen

Inhaltsverzeichnis

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
- Strategies for Global Deep Learning Forecasting Models
- Specialized Deep Learning Architectures for Forecasting
- Multi-Step Forecasting
- Evaluating Forecasts – Forecast Metrics
- Evaluating Forecasts – Validation Strategies

Über Autor(innen)

Joseph Manu:

Manu Joseph is a self-made data scientist with more than a decade of experience working with many Fortune 500 companies enabling digital and AI transformations, specifically in machine learning-based demand forecasting. He is considered an expert, thought leader, and strong voice in the world of time series forecasting. Currently, Manu leads applied research at Thoucentric, where he advances research by bringing cutting-edge AI technologies to the industry. He is also an active open-source contributor and developed an open-source library—PyTorch Tabular—which makes deep learning for tabular data easy and accessible. Originally from Thiruvananthapuram, India, Manu currently resides in Bengaluru, India, with his wife and son