Modern Time Series Forecasting Python 2nd Ed. by Manu Joseph (.ePUB)
File Size: 7.8 MB
Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas 2nd Edition by Manu Joseph (Author), Jeffrey Tackes (Author)
Requirements: .ePUB reader, 7.8 MB
Overview: Predicting the future, whether it’s market trends, energy demand, or website traffic, has never been more crucial. This practical, hands-on guide empowers you to build and deploy powerful time series forecasting models. With Modern Time Series Forecasting with Python, Second Edition, you’ll master cutting-edge deep learning architectures and advanced statistical techniques alongside classic methods like ARIMA and exponential smoothing. Learn the fundamentals from preprocessing, feature engineering, and evaluation to applying powerful machine and deep learning models, including ensemble and global methods.
This new edition goes deeper into transformer architectures and probabilistic forecasting, including new content on the latest time series models, conformal prediction, and hierarchical forecasting. Whether you seek advanced deep learning insights or specialized architecture implementations, this edition provides practical strategies and new content to elevate your forecasting skills.
Genre: Non-Fiction > Tech & Devices
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