Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
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Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
Unlock the potential of time series data with deep learning expertise using PyTorch and Python.
Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
Nº de artículo: 108807314

Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection

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Nº de artículo: 108807314

DOP 5377

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Detalles de producto

Shop Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection online at a best price in Dominican Republic. 1805129236
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

DESCRIPCIÓN DEL PRODUCTO

Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection

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Preguntas y respuestas de los clientes

  • Pregunta: What prior knowledge do I need to benefit from this book?

    Respuesta: A basic understanding of Python programming and machine learning is recommended.
  • Pregunta: Will I learn to use other deep learning frameworks in this book?

    Respuesta: This book focuses specifically on using PyTorch for deep learning in time series tasks.
  • Pregunta: What types of time series problems will I learn to solve?

    Respuesta: You'll tackle forecasting, classification, and anomaly detection problems using various deep neural network architectures.

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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ventajas

  • 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

Contras

  • Some users may find it too technical at times

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características y beneficios

  • 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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