£43.99

Packt Publishing Packt Modern Time Series Forecasting with Python Book

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Description

Master industry-ready machine learning and deep learning techniques with this comprehensive guide to time series analysis. Using PyTorch and pandas, you will learn to implement both traditional methods and cutting-edge architectures. This book covers essential topics such as global forecasting models, transformer architectures, and N-BEATS to improve your predictive accuracy. Develop advanced skills in probabilistic forecasting through practical applications of conformal prediction, Monte Carlo dropout, and quantile regression. Whether you are working with RNNs or modern deep learning models, this resource provides the tools needed for professional-grade forecasting. Every purchase includes a PDF copy, an AI assistant, and access to the Next-Gen Reader for an enhanced learning experience.

Key Features

Apply machine learning and global models to improve forecasting accuracy through practical, real-world examples.

Expand your technical toolkit by implementing deep learning models including RNNs, transformers, and N-BEATS.

Learn probabilistic forecasting techniques using conformal prediction, Monte Carlo dropout, and quantile regression.

Gain hands-on experience with industry-standard tools like PyTorch and pandas for time series analysis.

Access digital learning resources including a PDF copy, an AI assistant, and the Next-Gen Reader.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
31 October 2024
Listed Since
07 June 2024

Barcode

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