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108807314
Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
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Barang #:
108807314
USD 82
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Unlock the potential of time series data with deep learning expertise using PyTorch and Python.
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Rincian Produk
| Publisher | Packt Publishing |
| Publication date | 29 Mar. 2024 |
| Language | English |
| Print length | 304 pages |
| ISBN-10 | 1805129236 |
| ISBN-13 | 978-1805129233 |
| Item weight | 476 g |
| Dimensions | 19.05 x 1.57 x 23.5 cm |
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Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
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Higher Education Editorial Review
Deep Learning For Time Series Cookbook: Use PyTorch And Python Recipes For Forecasting, Classification, And Anomaly Detection offers practical applications and recipes for utilizing deep learning techniques effectively in time series analysis. The book, published by Packt Publishing, features 304 pages of insightful content, scheduled for release on 29 Mar. 2024, making it a timely addition for enthusiasts and professionals alike. Readers will appreciate the clear layout and accessible language, as it covers essential topics like forecasting and classification using PyTorch and Python. This makes it suitable for both beginners and advanced practitioners looking to enhance their skills in anomaly detection and other critical areas of time series data processing.
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Pro
- Comprehensive recipes for hands-on learning
- Covers key topics like anomaly detection
- Accessible language for all skill levels
- Structured layout enhances learning experience
- Focus on practical applications with PyTorch
Kontra
- Some users may find it too technical at times
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USD 82
Pesan sekarang dan dapatkan kira-kira pada Sabtu, Oktober 24
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Fitur & Manfaat
- Master time series analysis and modeling with deep learning.
- Utilize PyTorch to build advanced deep neural networks.
- Learn practical solutions for forecasting, classification, and anomaly detection.
- Includes free PDF eBook with purchase of print or Kindle version.
- Gain hands-on experience through easy-to-follow code recipes.
- Ideal for machine learning enthusiasts with basic Python knowledge.
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