Predicting Structured Data
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Predicting Structured Data
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Author : Neural Information Processing Systems Foundation
language : en
Publisher: MIT Press
Release Date : 2007
Predicting Structured Data written by Neural Information Processing Systems Foundation and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Algorithms categories.
State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.
Predicting Structured Data
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Author : Gökhan Bakir
language : en
Publisher: Mit Press
Release Date : 2007-07-27
Predicting Structured Data written by Gökhan Bakir and has been published by Mit Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-27 with categories.
Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must satisfy the additional constraints found in structured data, poses one of machine learning's greatest challenges: learning functional dependencies between arbitrary input and output domains. This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field. The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field. Contributors Yasemin Altun, Gökhan Bakir, Olivier Bousquet, Sumit Chopra, Corinna Cortes, Hal Daumé III, Ofer Dekel, Zoubin Ghahramani, Raia Hadsell, Thomas Hofmann, Fu Jie Huang, Yann LeCun, Tobias Mann, Daniel Marcu, David McAllester, Mehryar Mohri, William Stafford Noble, Fernando Pérez-Cruz, Massimiliano Pontil, Marc'Aurelio Ranzato, Juho Rousu, Craig Saunders, Bernhard Schölkopf, Matthias W. Seeger, Shai Shalev-Shwartz, John Shawe-Taylor, Yoram Singer, Alexander J. Smola, Sandor Szedmak, Ben Taskar, Ioannis Tsochantaridis, S.V.N Vishwanathan, Jason Weston.
Advanced Structured Prediction
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Author : Sebastian Nowozin
language : en
Publisher: MIT Press
Release Date : 2014-12-05
Advanced Structured Prediction written by Sebastian Nowozin and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-05 with Computers categories.
An overview of recent work in the field of structured prediction, the building of predictive machine learning models for interrelated and dependent outputs. The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components. These models are expressive and powerful, but exact computation is often intractable. A broad research effort in recent years has aimed at designing structured prediction models and approximate inference and learning procedures that are computationally efficient. This volume offers an overview of this recent research in order to make the work accessible to a broader research community. The chapters, by leading researchers in the field, cover a range of topics, including research trends, the linear programming relaxation approach, innovations in probabilistic modeling, recent theoretical progress, and resource-aware learning. Contributors Jonas Behr, Yutian Chen, Fernando De La Torre, Justin Domke, Peter V. Gehler, Andrew E. Gelfand, Sébastien Giguère, Amir Globerson, Fred A. Hamprecht, Minh Hoai, Tommi Jaakkola, Jeremy Jancsary, Joseph Keshet, Marius Kloft, Vladimir Kolmogorov, Christoph H. Lampert, François Laviolette, Xinghua Lou, Mario Marchand, André F. T. Martins, Ofer Meshi, Sebastian Nowozin, George Papandreou, Daniel Průša, Gunnar Rätsch, Amélie Rolland, Bogdan Savchynskyy, Stefan Schmidt, Thomas Schoenemann, Gabriele Schweikert, Ben Taskar, Sinisa Todorovic, Max Welling, David Weiss, Thomáš Werner, Alan Yuille, Stanislav Živný
Linguistic Structure Prediction
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Author : Noah A. Smith
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Linguistic Structure Prediction written by Noah A. Smith and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. We also survey natural language processing problems to which these methods are being applied, and we address related topics in probabilistic inference, optimization, and experimental methodology. Table of Contents: Representations and Linguistic Data / Decoding: Making Predictions / Learning Structure from Annotated Data / Learning Structure from Incomplete Data / Beyond Decoding: Inference
Forecasting Intelligence A Practical Guide To Predicting Success
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-03-07
Forecasting Intelligence A Practical Guide To Predicting Success written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-07 with Business & Economics categories.
In a world characterized by constant change and uncertainty, the ability to accurately predict future events has become an invaluable asset. Forecasting Intelligence: A Practical Guide to Predicting Success is your comprehensive roadmap to navigating the complexities of forecasting, empowering you to make informed decisions and seize opportunities in an ever-shifting landscape. This book is not just a collection of technical methods and theories; it's an invitation to develop a forecasting mindset that embraces uncertainty, cultivates critical thinking, and values the power of collaboration. Through engaging case studies and real-world examples, Forecasting Intelligence brings the world of forecasting to life, demonstrating its practical applications across diverse fields. Whether you're a business leader seeking to anticipate market trends, a policymaker aiming to mitigate risks, or an individual planning for the future, this book offers invaluable insights into the art and science of forecasting. Discover the secrets of successful forecasters, learn from both triumphs and failures, and gain the confidence to make informed decisions based on data-driven insights. Forecasting Intelligence takes you on an enlightening journey, exploring the foundational principles of forecasting, cutting-edge techniques and methodologies, and the challenges and opportunities that lie ahead. You'll discover how to: * Harness the power of probability theory and time series analysis to make accurate predictions * Overcome the challenges of incomplete data, non-stationary patterns, and rare events * Effectively communicate forecast results to stakeholders and decision-makers * Navigate the ethical and societal implications of forecasting * Develop a forecasting mindset that embraces uncertainty and values continuous learning With Forecasting Intelligence as your guide, you'll gain the knowledge and skills necessary to make informed predictions, empowering you to thrive in an increasingly interconnected and unpredictable world. Embrace the future with confidence, knowing that you have the tools and strategies to navigate its uncertainties and achieve success. If you like this book, write a review!
Deep Learning With Structured Data
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Author : Mark Ryan
language : en
Publisher: Simon and Schuster
Release Date : 2020-12-08
Deep Learning With Structured Data written by Mark Ryan and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-08 with Computers categories.
Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Summary Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Here’s a dirty secret: Half of the time in most data science projects is spent cleaning and preparing data. But there’s a better way: Deep learning techniques optimized for tabular data and relational databases deliver insights and analysis without requiring intense feature engineering. Learn the skills to unlock deep learning performance with much less data filtering, validating, and scrubbing. About the book Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Get started using a dataset based on the Toronto transit system. As you work through the book, you’ll learn how easy it is to set up tabular data for deep learning, while solving crucial production concerns like deployment and performance monitoring. What's inside When and where to use deep learning The architecture of a Keras deep learning model Training, deploying, and maintaining models Measuring performance About the reader For readers with intermediate Python and machine learning skills. About the author Mark Ryan is a Data Science Manager at Intact Insurance. He holds a Master's degree in Computer Science from the University of Toronto. Table of Contents 1 Why deep learning with structured data? 2 Introduction to the example problem and Pandas dataframes 3 Preparing the data, part 1: Exploring and cleansing the data 4 Preparing the data, part 2: Transforming the data 5 Preparing and building the model 6 Training the model and running experiments 7 More experiments with the trained model 8 Deploying the model 9 Recommended next steps
Data Analytics And Artificial Intelligence For Predictive Maintenance In Smart Manufacturing
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Author : Amit Kumar Tyagi
language : en
Publisher: CRC Press
Release Date : 2024-10-23
Data Analytics And Artificial Intelligence For Predictive Maintenance In Smart Manufacturing written by Amit Kumar Tyagi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-23 with Computers categories.
Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields.
Medinfo 2019 Health And Wellbeing E Networks For All
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Author : L. Ohno-Machado
language : en
Publisher: IOS Press
Release Date : 2019-11-12
Medinfo 2019 Health And Wellbeing E Networks For All written by L. Ohno-Machado and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-12 with Medical categories.
Combining and integrating cross-institutional data remains a challenge for both researchers and those involved in patient care. Patient-generated data can contribute precious information to healthcare professionals by enabling monitoring under normal life conditions and also helping patients play a more active role in their own care. This book presents the proceedings of MEDINFO 2019, the 17th World Congress on Medical and Health Informatics, held in Lyon, France, from 25 to 30 August 2019. The theme of this year’s conference was ‘Health and Wellbeing: E-Networks for All’, stressing the increasing importance of networks in healthcare on the one hand, and the patient-centered perspective on the other. Over 1100 manuscripts were submitted to the conference and, after a thorough review process by at least three reviewers and assessment by a scientific program committee member, 285 papers and 296 posters were accepted, together with 47 podium abstracts, 7 demonstrations, 45 panels, 21 workshops and 9 tutorials. All accepted paper and poster contributions are included in these proceedings. The papers are grouped under four thematic tracks: interpreting health and biomedical data, supporting care delivery, enabling precision medicine and public health, and the human element in medical informatics. The posters are divided into the same four groups. The book presents an overview of state-of-the-art informatics projects from multiple regions of the world; it will be of interest to anyone working in the field of medical informatics.
Understanding The Complex Phenomenon Of Suicide From Research To Clinical Practice Volume Ii
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Author : Domenico De Berardis
language : en
Publisher: Frontiers Media SA
Release Date : 2022-08-29
Understanding The Complex Phenomenon Of Suicide From Research To Clinical Practice Volume Ii written by Domenico De Berardis and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-29 with Medical categories.
Recent Developments In Microbiology Biotechnology And Pharmaceutical Sciences
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Author : B. Sundaravadivazhagan
language : en
Publisher: CRC Press
Release Date : 2025-05-06
Recent Developments In Microbiology Biotechnology And Pharmaceutical Sciences written by B. Sundaravadivazhagan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-06 with Technology & Engineering categories.
The Conference brought together innovative academics and industrial experts in the field of Medical, Biological and Pharmaceutical Sciences to a common forum. The primary goal of the conference was to promote research and developmental activities in Medical, Biological and Pharmaceutical Sciences. Another goal was to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world.