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Can I read Modern Time Series Forecasting with Python: Industry-Ready Machine Learning and Deep Learning Time Series Analysis with PyTorch and Pandas on EtoBox?
Modern Time Series Forecasting with Python: Industry-Ready Machine Learning and Deep Learning Time Series Analysis with PyTorch and Pandas by MANU. TACKES JOSEPH (JEFFREY.) is a nonfiction available to read on EtoBox.
What is Modern Time Series Forecasting with Python: Industry-Ready Machine Learning and Deep Learning Time Series Analysis with PyTorch and Pandas about?
Learn traditional and cutting-edge machine learning (ML) and deep learning techniques and best practices for time series forecasting, including global forecasting models, conformal prediction, and transformer architectures Key Features Apply ML and global models to improve forecasting accuracy through practical examples Enhance your time series toolkit by using deep learning models, including RNNs, transformers, and N-BEATS Learn probabilistic forecasting with conformal prediction, Monte Carlo dropout, and quantile regressions Purchase of the print or Kindle book includes a free eBook in PDF format Book Description 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. Whether you’re working with traditional statistical methods or cutting-edge deep learning architectures, this book provides structured learning and best practices for both. Starting with the basics, this data science book introduces fundamental time series concepts, such as ARIMA and exponential smoothing, before gradually progressing to advanced topics,
Who reads Modern Time Series Forecasting with Python: Industry-Ready Machine Learning and Deep Learning Time Series Analysis with PyTorch and Pandas?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- MANU. TACKES JOSEPH (JEFFREY.)
- Publisher
- Packt Publishing - ebooks Account
- Published
- 2024
- Language
- EN
- ISBN
- 9781835883181
- Category
- nonfiction
- Subjects
- Mathematics, Computer Science, Stem
Other editions & translations
- Time Series Indexing: Implement iSAX in Python to index time series with confidence (2022)
- Modern Time Series Forecasting with Python : Explore Industry-ready Time Series Forecasting Using Modern Machine Learning and Deep Learning (2022)
- Modern Time Series Forecasting with Python - Second Edition (Early Access) (2024)
- Forecasting Time Series Data with Prophet: Build, improve, and optimize time series forecasting models using Meta's advanced forecasting tool, 2nd Edition (2023)
- Modern Time Series Forecasting with Python (Early Release) (2024)
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