Time Series Forecasting Using Generative Ai

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Time Series Forecasting Using Generative Ai

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Author : Vishwas B V
language : en
Publisher: Apress
Release Date : 2025-04-07

Time Series Forecasting Using Generative Ai written by Vishwas B V and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-07 with Computers categories.

"Time Series Forecasting Using Generative AI introduces readers to Generative Artificial Intelligence (Gen AI) in time series analysis, offering an essential exploration of cutting-edge forecasting methodologies." The book covers a wide range of topics, starting with an overview of Generative AI, where readers gain insights into the history and fundamentals of Gen AI with a brief introduction to large language models. The subsequent chapter explains practical applications, guiding readers through the implementation of diverse neural network architectures for time series analysis such as Multi-Layer Perceptrons (MLP), WaveNet, Temporal Convolutional Network (TCN), Bidirectional Temporal Convolutional Network (BiTCN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Deep AutoRegressive(DeepAR), and Neural Basis Expansion Analysis(NBEATS) using modern tools. Building on this foundation, the book introduces the power of Transformer architecture, exploring its variants such as Vanilla Transformers, Inverted Transformer (iTransformer), DLinear, NLinear, and Patch Time Series Transformer (PatchTST). Finally, The book delves into foundation models such as Time-LLM, Chronos, TimeGPT, Moirai, and TimesFM enabling readers to implement sophisticated forecasting models tailored to their specific needs. This book empowers readers with the knowledge and skills needed to leverage Gen AI for accurate and efficient time series forecasting. By providing a detailed exploration of advanced forecasting models and methodologies, this book enables practitioners to make informed decisions and drive business growth through data-driven insights. Understand the core concepts, history, and applications of Gen AI and its potential to revolutionize time series forecasting. Learn to implement different neural network architectures such as MLP, WaveNet, RNN, LSTM, DeepAR, and NBEATS for time series forecasting. Discover the potential of Transformer architecture and its variants, such as Vanilla Transformers, iTransformer, and PatchTST, for time series forecasting. Explore complex foundation models like Time-LLM, Chronos, TimeGPT, Moirai, and TimesFM. How to apply Gen AI techniques to real-world time series forecasting challenges and make data-driven decisions. Who this book is for: Data Scientists, Machine learning engineers, Business Aanalysts, Statisticians, Economists, Financial Analysts, Operations Research Analysts, Data Analysts, Students.

Time Series Forecasting Using Generative Ai

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Author : Banglore Vijay Kumar Vishwas
language : en
Publisher: Springer Nature
Release Date : 2025-03-24

Time Series Forecasting Using Generative Ai written by Banglore Vijay Kumar Vishwas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-24 with Mathematics categories.

"Time Series Forecasting Using Generative AI introduces readers to Generative Artificial Intelligence (Gen AI) in time series analysis, offering an essential exploration of cutting-edge forecasting methodologies." The book covers a wide range of topics, starting with an overview of Generative AI, where readers gain insights into the history and fundamentals of Gen AI with a brief introduction to large language models. The subsequent chapter explains practical applications, guiding readers through the implementation of diverse neural network architectures for time series analysis such as Multi-Layer Perceptrons (MLP), WaveNet, Temporal Convolutional Network (TCN), Bidirectional Temporal Convolutional Network (BiTCN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Deep AutoRegressive(DeepAR), and Neural Basis Expansion Analysis(NBEATS) using modern tools. Building on this foundation, the book introduces the power of Transformer architecture, exploring its variants such as Vanilla Transformers, Inverted Transformer (iTransformer), DLinear, NLinear, and Patch Time Series Transformer (PatchTST). Finally, The book delves into foundation models such as Time-LLM, Chronos, TimeGPT, Moirai, and TimesFM enabling readers to implement sophisticated forecasting models tailored to their specific needs. This book empowers readers with the knowledge and skills needed to leverage Gen AI for accurate and efficient time series forecasting. By providing a detailed exploration of advanced forecasting models and methodologies, this book enables practitioners to make informed decisions and drive business growth through data-driven insights. !-- [if !supportLists]--● !--[endif]--Understand the core history and applications of Gen AI and its potential to revolutionize time series forecasting. !-- [if !supportLists]--● !--[endif]--Learn to implement different neural network architectures such as MLP, WaveNet, TCN, BiTCN, RNN, LSTM, DeepAR, and NBEATS for time series forecasting. !-- [if !supportLists]--● !--[endif]--Discover the potential of Transformer architecture and its variants, such as Vanilla Transformers, iTransformer, DLinear, NLinear, and PatchTST, for time series forecasting. !-- [if !supportLists]--● !--[endif]--Explore complex foundation models like Time-LLM, Chronos, TimeGPT, Moirai, and TimesFM. !-- [if !supportLists]--● !--[endif]--Gain practical knowledge on how to apply Gen AI techniques to real-world time series forecasting challenges and make data-driven decisions. Who this book is for: Data Scientists, Machine learning engineers, Business Aanalysts, Statisticians, Economists, Financial Analysts, Operations Research Analysts, Data Analysts, Students.

Time Series Analysis With Spark

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Author : Yoni Ramaswami
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-03-28

Time Series Analysis With Spark written by Yoni Ramaswami and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-28 with Computers categories.

Master the fundamentals of time series analysis with Apache Spark and Databricks and uncover actionable insights at scale Key Features Quickly get started with your first models and explore the potential of Generative AI Learn how to use Apache Spark and Databricks for scalable time series solutions Establish best practices to ensure success from development to production and beyond Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by Databricks Senior Solutions Architect Yoni Ramaswami, whose expertise in Data and AI has shaped innovative digital transformations across industries, this comprehensive guide bridges foundational concepts of time series analysis with the Spark framework and Databricks, preparing you to tackle real-world challenges with confidence. From preparing and processing large-scale time series datasets to building reliable models, this book offers practical techniques that scale effortlessly for big data environments. You’ll explore advanced topics such as scaling your analyses, deploying time series models into production, Generative AI, and leveraging Spark's latest features for cutting-edge applications across industries. Packed with hands-on examples and industry-relevant use cases, this guide is perfect for data engineers, ML engineers, data scientists, and analysts looking to enhance their expertise in handling large-scale time series data. By the end of this book, you’ll have mastered the skills to design and deploy robust, scalable time series models tailored to your unique project needs—qualifying you to excel in the rapidly evolving world of big data analytics.What you will learn Understand the core concepts and architectures of Apache Spark Clean and organize time series data Choose the most suitable modeling approach for your use case Gain expertise in building and training a variety of time series models Explore ways to leverage Apache Spark and Databricks to scale your models Deploy time series models in production Integrate your time series solutions with big data tools for enhanced analytics Leverage GenAI to enhance predictions and uncover patterns Who this book is for If you are a data engineer, ML engineer, data scientist, or analyst looking to enhance your skills in time series analysis with Apache Spark and Databricks, this book is for you. Whether you’re new to time series or an experienced practitioner, this guide provides valuable insights and techniques to improve your data processing capabilities. A basic understanding of Apache Spark is helpful, but no prior experience with time series analysis is required.

Statistics For Innovation Iv

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Author : Enrico di Bella
language : en
Publisher: Springer Nature
Release Date : 2025-06-16

Statistics For Innovation Iv written by Enrico di Bella and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-16 with Mathematics categories.

This book presents peer-reviewed short papers on methodological and applied statistical research presented at the Italian Statistical Society’s international conference on “Statistics for Innovation”, SIS 2025, held in Genoa, Italy, June 16-18, 2025. It is the last of four volumes, featuring the third part of the contributions presented in the Contributed Sessions. Providing a comprehensive overview of innovations in modern statistical methods and applications, the volumes address a large number of topics of current interest, contributing to a rapid dissemination of quantitative methods for data analysis across the various fields of scientific research and social life. The volumes underpin the role of statistics and data science in fostering innovation in numerous fields, including business, industry, finance, technology, environment, health and medicine, official statistics, public policy, welfare, social issues and sustainable development. One of the aims of the Italian Statistical Society (SIS) is to promote scientific activities for the development of statistical sciences. Together with the biennial international Scientific Meeting, the intermediate international statistical conferences on a particular topic of interest represent the Society’s most important events which bring together national and international researchers and professionals to exchange ideas and discuss recent advances and developments in theoretical and applied statistics.

Data Analysis For Business Decisions

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Author : Andres Fortino
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2025-01-04

Data Analysis For Business Decisions written by Andres Fortino and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-04 with Computers categories.

In today’s data-driven world, the ability to analyze and interpret data is no longer optional—it’s a necessity for making informed business decisions. This book provides a comprehensive, hands-on guide to mastering the essential techniques and tools that empower business analysts to transform raw data into actionable insights. Packed with practical exercises and real-world case studies, this book focuses on applying statistical methods across the most widely used tools, including Excel, R, Python, and generative AI platforms like ChatGPT. Key topics include framing analytical questions, descriptive and advanced statistical techniques, text analytics and A/B testing, and big data and visualization. Whether analyzing sales trends, optimizing marketing strategies, or improving operational efficiency, you’ll gain the skills to make data-backed decisions that drive business success. FEATURES • Includes hands-on exercises with industry-standard tools, including Excel, R, Python, and generative AI • Covers step-by-step instructions for advanced techniques like time series forecasting and contingency analysis • Uses real-world case studies to demonstrate the application of concepts to business scenarios • Features companion files with datasets, surveys, and cases (available for downloading from the publisher)

Progress In Artificial Intelligence

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Author : Manuel Filipe Santos
language : en
Publisher: Springer Nature
Release Date : 2024-11-15

Progress In Artificial Intelligence written by Manuel Filipe Santos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-15 with Computers categories.

The 3-volume set LNAI 14967, 14968, and 14969 constitutes the proceedings of the 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, held in Viana do Castelo, Portugal, during September 3–6, 2024. The 94 full papers presented in these proceedings were carefully reviewed and selected from 187 submissions. The papers are organized in the following topical sections: Volume I: AI and Creativity (AIC); Ambient Intelligence and Affective Environments (AmIA); Artificial Intelligence and IoT in Agriculture (AIoTA); Artificial Intelligence and Law (AIL); and Artificial Intelligence for Industry and Societies (AI4IS). Volume II: Artificial Intelligence in Medicine (AIM); Artificial Intelligence in Power and Energy Systems (AIPES); Artificial Intelligence in Transportation Systems (AITS); Ethics and Responsibility in AI (ERAI); and General AI (GAI). Volume III: Generative AI – Foundations and Applications (GenAI); Intelligent Robotics (IROBOT); Knowledge Discovery and Business Intelligence (KDBI); Natural Language Processing, Text Mining and Applications (TeMA); and Data-Centric AI – Solutions and Emerging Technologies (DCenAI).

Advances In Information Retrieval

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Author : Claudia Hauff
language : en
Publisher: Springer Nature
Release Date : 2025-04-02

Advances In Information Retrieval written by Claudia Hauff and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-02 with Computers categories.

The five-volume set LNCS 15572, 15573, 15574, 15575 and 15576 constitutes the refereed conference proceedings of the 47th European Conference on Information Retrieval, ECIR 2025, held in Lucca, Italy, during April 6–10, 2025. The 52 full papers, 11 findings, 42 short papers and 76 papers of other types presented in these proceedings were carefully reviewed and selected from 530 submissions. The accepted papers cover the state-of-the-art in information retrieval and recommender systems: user aspects, system and foundational aspects, artificial intelligence and machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search and recommendation.

Generative Ai In Food Systems Predictive Demand Smart Supply Chains And Sustainable Service Futures

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Author : Madaan, Geetika
language : en
Publisher: IGI Global
Release Date : 2025-06-20

Generative Ai In Food Systems Predictive Demand Smart Supply Chains And Sustainable Service Futures written by Madaan, Geetika and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-20 with Technology & Engineering categories.

Generative AI has emerged as a powerful tool in reshaping food systems. By leveraging vast datasets and advanced algorithms, generative AI enables businesses to anticipate market trends, reduce food waste, and tailor offerings to shifting consumer preferences with unprecedented precision. As industry faces mounting pressures from climate change, population growth, and evolving consumption habits, generative AI presents a transformative opportunity to build resilient, sustainable, and forward-looking food systems. Generative AI in Food Systems: Predictive Demand, Smart Supply Chains, and Sustainable Service Futures explores how generative AI has revolutionized food supply chains and how it can create a more efficient system. This book investigates the intersection of generative AI and food supply chain management. Covering topics such as food systems, AI, and supply chain management, this book is an excellent resource for academics, policymakers, and technology developers.

Algorithms In Advanced Artificial Intelligence

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Author : R. N. V. Jagan Mohan
language : en
Publisher: CRC Press
Release Date : 2024-07-08

Algorithms In Advanced Artificial Intelligence written by R. N. V. Jagan Mohan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-08 with Computers categories.

The most common form of severe dementia, Alzheimer’s disease (AD), is a cumulative neurological disorder because of the degradation and death of nerve cells in the brain tissue, intelligence steadily declines and most of its activities are compromised in AD. Before diving into the level of AD diagnosis, it is essential to highlight the fundamental differences between conventional machine learning (ML) and deep learning (DL). This work covers a number of photo-preprocessing approaches that aid in learning because image processing is essential for the diagnosis of AD. The most crucial kind of neural network for computer vision used in medical image processing is called a Convolutional Neural Network (CNN). The proposed study will consider facial characteristics, including expressions and eye movements using the diffusion model, as part of CNN’s meticulous approach to Alzheimer’s diagnosis. Convolutional neural networks were used in an effort to sense Alzheimer’s disease in its early stages using a big collection of pictures of facial expressions.

Exploring The Ethical Implications Of Generative Ai

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Author : Ara, Aftab
language : en
Publisher: IGI Global
Release Date : 2024-04-04

Exploring The Ethical Implications Of Generative Ai written by Ara, Aftab and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-04 with Computers categories.

Generative Artificial Intelligence (AI), an ever-evolving technology, holds immense promise across various industries, from healthcare to content generation. However, its rapid advancement has also given rise to profound ethical concerns. Illicit black-market industries exploit generative AI for counterfeit imagery, and in educational settings, biases and misinformation perpetuate. These issues underscore the need to grapple with the risks accompanying generative AI integration. Exploring the Ethical Implications of Generative AI emerges as a wellspring of insight for discerning academic scholars. It sets the stage by acknowledging generative AI's multifaceted potential and its capacity to reshape industries. The book addresses these complex ethical concerns, offering a comprehensive analysis and providing a roadmap for responsible AI development and usage. Its intended audience spans business leaders, policymakers, scholars, and individuals passionate about the ethical dimensions of AI.