Transformers for Time Series Forecasting. Modern techniques for time series forecasting, classification, and anomaly detection with transformers

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Autor:: Gerzson David Boros

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Transformers for Time Series Forecasting. Modern techniques for time series forecasting, classification, and anomaly detection with transformers Gerzson David Boros - okladka książki

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Wydawnictwo:: Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
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Generative AI has profoundly changed the world, and Transformers are a crucial instrument in this process. However, the application of Transformers for time series hasn't been widely adopted yet, despite the immense potential in this field. Transformers, among other things, possess the ability to identify long-range dependencies and interactions in the data.

In the Transformers for Time Series Forecasting book, the most recent research findings are presented in a highly practical fashion. Utilizing real-life projects and employing PyTorch and TensorFlow, the reader is guided through various use cases. Starting with the most commonly utilised applications for time series data, such as forecasting and classification, the book introduces the reader to both the theory and implementation. Later, more specialised cases are covered, including anomaly detection, event forecasting, and spatio-temporal modelling.

The final chapters introduce how to improve these algorithms further, what the best practices are, how to optimise with hyperparameter tuning techniques and architecture-level modifications. Lastly, we discuss how to scale transformer-based solutions when dealing with large amounts of data.

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O autorze książki

Gerzson David Boros is the owner and CEO of Data Science Europe, Lead Data Scientist and Freelancer who has been involved in data science and AI for more than 10 years. He has an MSc and a candidate for MBA in AI. He is an instructor at Udemy and IIITB via Upgrad. He holds online courses for Deep Learning and MLOps in a Postgraduate Program in ML and AI.
He worked at Siemens Group as Lead Data Scientist, then in the last 5 years, he worked on more than 30 different projects for AI development successfully for different startups from USA, Europe and Asia. His motto is “Social responsibility is also achievable with the help of data.” In his spare time, Gerzson is a proud husband and father, a professional drummer, and he enjoys traveling.

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Szczegóły książki

Tytuł oryginału:: Transformers for Time Series Forecasting. Modern techniques for time series forecasting, classification, and anomaly detection with transformers
ISBN Ebooka:: 978-18-051-2203-6, 9781805122036
Data wydania ebooka :: 2024-08-21 Data wydania ebooka często jest dniem wprowadzenia tytułu do sprzedaży i może nie być równoznaczna z datą wydania książki papierowej. Dodatkowe informacje możesz znaleźć w darmowym fragmencie. Jeśli masz wątpliwości skontaktuj się z nami sklep@helion.pl.
Język publikacji:: 1

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Kategorie:
Sztuczna inteligencja

Spis treści książki

1. Time Series Analysis: Challenges
2. Transformers for Time Series
3. Time Series Forecasting with Transformers
4. Transformers for Time Series Classification
5. Spatio-Temporal Modelling leveraging Transformers
6. Event Forecasting using Transformers
7. Applying Transformers for Time Series Anomaly Detection
8. Tips, Best Practices for Efficient Transformer Implementation
9. Hyperparameter tuning, Architecture-level Modifications, AutoML, NAS (Neural Architecture Search)
10. Scaling Transformers

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