Deep Leaing for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
by: Vitor Cerqueira(Author),Luís Roque(Author)
Publisher: Packt Publishing
Publication Date: 29 Mar. 2024
Language: English
Print Length: 274 pages
ISBN-10: 1805129236
ISBN-13: 9781805129233
Book Description
Lea how to deal with time series data and how to model it using deep leaing and take your skills to the next level by mastering PyTorch using different Python recipesKey FeaturesLea the fundamentals of time series analysis and how to model time series data using deep leaingExplore the world of deep leaing with PyTorch and build advanced deep neural networksGain expertise in tackling time series problems, from forecasting future trends to classifying pattes and anomaly detectionPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMost 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 leaing can process large amounts of data and help derive complex pattes. Despite its increasing relevance, getting the most out of deep leaing requires significant technical expertise.This book guides you through applying deep leaing 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 leaing 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 leaing framework based on Python to build production-ready prediction solutions.By the end of this book, you’ll have leaed how to solve different time series tasks with deep leaing using the PyTorch ecosystem.What you will leaGrasp the core of time series analysis and unleash its power using PythonUnderstand PyTorch and how to use it to build deep leaing modelsDiscover how to transform a time series for training transformersUnderstand how to deal with various time series characteristicsTackle forecasting problems, involving univariate or multivariate dataMaster time series classification with residual and convolutional neural networksGet up to speed with solving time series anomaly detection problems using autoencoders and generative adversarial networks (GANs)Who this book is forIf you’re a machine leaing enthusiast or someone who wants to lea more about building forecasting applications using deep leaing, this book is for you. Basic knowledge of Python programming and machine leaing is required to get the most out of this book.Table of ContentsGetting Started with Time SeriesGetting Started with PyTorchUnivariate Time Series ForecastingForecasting with PyTorch LightningGlobal Forecasting ModelsAdvanced Deep Leaing Architectures for Time Series ForecastingProbabilistic Time Series ForecastingDeep Leaing for Time Series ClassificationDeep Leaing for Time Series Anomaly Detection
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