Small quarto, softcover, new in black pictorial wraps. 253 pp. first edition. In senior management, you no longer answer to just one boss. There is now a hazy matrix of hundreds of bosses both inside and outside the office, any one of whom can stop you cold or give you a tremendous push forward. Executive Warfare offers concrete advice for handling all of them, including your peers, the CEO, board of directors, direct reports, your rivals.

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Detalles bibliogr�ficos

T�tulo: Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
Editor: Packt Publishing
Fecha de publicaci�n: 2024
Idioma: Ingl�s
ISBN 10: 1805129236
ISBN 13: 9781805129233
Encuadernaci�n: Soft cover
Estado: New

Acerca de

Sinopsis

Learn how to deal with time series data and how to model it using deep learning and take your skills to the next level by mastering PyTorch using different Python recipes

Key Features

Learn the fundamentals of time series analysis and how to model time series data using deep learning
Explore the world of deep learning with PyTorch and build advanced deep neural networks
Gain expertise in tackling time series problems, from forecasting future trends to classifying patterns and anomaly detection
Purchase of the print or Kindle book includes a free PDF eBook

Book Description

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.

What you will learn

Grasp the core of time series analysis and unleash its power using Python
Understand PyTorch and how to use it to build deep learning models
Discover how to transform a time series for training transformers
Understand how to deal with various time series characteristics
Tackle forecasting problems, involving univariate or multivariate data
Master time series classification with residual and convolutional neural networks
Get up to speed with solving time series anomaly detection problems using autoencoders and generative adversarial networks (GANs)

Who this book is for

If you're a machine learning enthusiast or someone who wants to learn more about building forecasting applications using deep learning, this book is for you. Basic knowledge of Python programming and machine learning is required to get the most out of this book.

Getting Started with Time Series
Getting Started with PyTorch
Univariate Time Series Forecasting
Forecasting with PyTorch Lightning
Global Forecasting Models
Advanced Deep Learning Architectures for Time Series Forecasting
Probabilistic Time Series Forecasting
Deep Learning for Time Series Classification
Deep Learning for Time Series Anomaly Detection

Acerca de los autores

Vitor Cerqueira is a time series researcher with an extensive background in machine learning. Vitor obtained his Ph.D. degree in Software Engineering from the University of Porto in 2019. He is currently a Post-Doctoral researcher in Dalhousie University, Halifax, developing machine learning methods for time series forecasting. Vitor has co-authored several scientific articles that have been published in multiple high-impact research venues.

Lu�s 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. Lu�s 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.

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I have a large inventory of children's books, cookbooks, collectibles, classics, first editions, signed books, history, biographies, science, textbooks, and more. Each book to me is a "precious jewel" and I try and describe it, giving you a good understanding of its content, and also its condition. One example, I have a John Muir book where he has written in the margins all through it to correct mistakes made by the publisher. (this was confirmed by John Muir historic site for me) I have over 50,000 books and some are quite rare from 1800's to 2020's. I've been collecting books for over 50 years and now am a spry 80 and going strong. I try and get books out same day as order comes in and love it when someone writes that they's been looking for a book for years and finally found it with me!

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