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- Herausgeber: Packt Publishing
- Kategorie: Lebensstil
- Sprache: Englisch
Most organizations exhibit a time-dependent structure in their processes, including fields such as finance. By leveraging time series analysis and forecasting, these organizations can make informed decisions and optimize their performance. Accurate forecasts help reduce uncertainty and enable better planning of operations. Unlike traditional approaches to forecasting, deep learning can process large amounts of data and help derive complex patterns. Despite its increasing relevance, getting the most out of deep learning requires significant technical expertise.
This book guides you through applying deep learning to time series data with the help of easy-to-follow code recipes. You’ll cover time series problems, such as forecasting, anomaly detection, and classification. This deep learning book will also show you how to solve these problems using different deep neural network architectures, including convolutional neural networks (CNNs) or transformers. As you progress, you’ll use PyTorch, a popular deep learning framework based on Python to build production-ready prediction solutions.
By the end of this book, you'll have learned how to solve different time series tasks with deep learning using the PyTorch ecosystem.
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Seitenzahl: 269
Veröffentlichungsjahr: 2024
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Deep Learning for Time Series Cookbook
Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
Vitor Cerqueira
Luís Roque
Deep Learning for Time Series Cookbook
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ISBN 978-1-80512-923-3
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Contributors
About the authors
Vitor Cerqueira is a machine learning researcher at the Faculty of Engineering at the University of Porto, working on a variety of projects concerning time-series data, including forecasting, anomaly detection, and meta-learning. Vitor earned his Ph.D. with honors, also from the University of Porto, and he also has a background in data analytics and mathematics. He has authored several peer-reviewed publications on related topics.
Luís Roque, is the Founder and Partner of ZAAI, a company focused on AI product development, consultancy, and investment in AI startups. He also serves as the Vice President of Data & AI at Marley Spoon, leading teams across data science, data analytics, data product, data engineering, machine learning operations, and platforms.
In addition, he holds the position of AI Advisor at CableLabs, where he contributes to integrating the broadband industry with AI technologies.
Luís is also a Ph.D. Researcher in AI at the University of Porto's AI&CS lab and oversees the Data Science Master's program at Nuclio Digital School in Barcelona. Previously, he co-founded HUUB, where he served as CEO until its acquisition by Maersk.
About the reviewer
Tuhin Sharma is a senior principal data scientist at Red Hat in the corporate development and strategy group. Prior to that, he worked at Hypersonix as an AI architect. He also co-founded and has been CEO of Binaize, a website conversion intelligence product for e-commerce SMBs. He received a master’s degree from IIT in Roorkee and a bachelor’s degree in computer science from IIEST in Shibpur. He loves to code and collaborate on open source and research projects. He has four research papers and five patents in the field of AI and NLP. He is a reviewer of the IEEE MASS conference in the AI track. He writes deep learning articles for O’Reilly in collaboration with the AWS MXNet team. He is a regular speaker at prominent AI conferences such as O’Reilly AI, ODSC, and GIDS.
