Visualization For Artificial Intelligence
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Visualization For Artificial Intelligence
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Author : Shixia Liu
language : en
Publisher: Springer Nature
Release Date : 2024-12-21
Visualization For Artificial Intelligence written by Shixia Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-21 with Computers categories.
This book explores how visualization provides an effective way of improving not only the interpretability but also the generalization capabilities of machine learning models. It shows how visualization can bridge the gap between complex models or algorithms and human understanding while also facilitating data curation and model refinement. Therefore, visualization for artificial intelligence (VIS4AI) has become an emerging area that combines interactive visualization with machine learning techniques to maximize their values. VIS4AI techniques focus on every phase of the machine learning life cycle, from data preprocessing to model development and deployment. These techniques are closely aligned with the well-established data and model pipelines in machine learning. In the data pipeline, they contribute to improving data quality and feature quality, including training data cleaning and feature engineering. In the model pipeline, they support (1) model development by focusing on model understanding, diagnosis, and steering; and (2) model deployment by enabling decision explanation, model performance monitoring, and model maintenance. This book provides a framework of VIS4AI and introduces the associated techniques in the two pipelines. It emphasizes the importance of interactive visualization in AI and presents various visualization techniques for different purposes. It also discusses the challenges and opportunities of VIS4AI and proposes several promising research topics for future work, such as improving training data using complementary modalities, online training diagnosis, fitting the dynamic nature of AI systems, and interactively pre-training and adapting foundation models. Overall, this book aims to serve as a resource for researchers and practitioners interested in both visualization and artificial intelligence.
Machine Learning Concepts Tools And Data Visualization
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Author : Minsoo Kang
language : en
Publisher: World Scientific
Release Date : 2021-03-16
Machine Learning Concepts Tools And Data Visualization written by Minsoo Kang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-16 with Computers categories.
This set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important concepts in the field of machine learning. It consists of three parts. The first is an overview of the history of artificial intelligence, machine learning, and data science, and also includes case studies of well-known AI systems. The second is a step-by-step introduction to Azure Machine Learning, with examples provided. The third is an explanation of the techniques and methods used in data visualization with R, which can be used to communicate the results collected by the AI systems when they are analyzed statistically. Practice questions are provided throughout the book.
Integrating Artificial Intelligence And Visualization For Visual Knowledge Discovery
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Author : Boris Kovalerchuk
language : en
Publisher: Springer Nature
Release Date : 2022-06-04
Integrating Artificial Intelligence And Visualization For Visual Knowledge Discovery written by Boris Kovalerchuk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-04 with Technology & Engineering categories.
This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.
Artificial Intelligence And Visualization Advancing Visual Knowledge Discovery
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Author : Boris Kovalerchuk
language : en
Publisher: Springer Nature
Release Date : 2024-04-24
Artificial Intelligence And Visualization Advancing Visual Knowledge Discovery written by Boris Kovalerchuk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-24 with Computers categories.
This book continues a series of Springer publications devoted to the emerging field of Integrated Artificial Intelligence and Machine Learning with Visual Knowledge Discovery and Visual Analytics that combine advances in both fields. Artificial Intelligence and Machine Learning face long-standing challenges of explainability and interpretability that underpin trust. Such attributes are fundamental to both decision-making and knowledge discovery. Models are approximations and, at best, interpretations of reality that are transposed to algorithmic form. A visual explanation paradigm is critically important to address such challenges, as current studies demonstrate in salience analysis in deep learning for images and texts. Visualization means are generally effective for discovering and explaining high-dimensional patterns in all high-dimensional data, while preserving data properties and relations in visualizations is challenging. Recent developments, such as in General Line Coordinates, open new opportunities to address such challenges. This book contains extended papers presented in 2021 and 2022 at the International Conference on Information Visualization (IV) on AI and Visual Analytics, with 18 chapters from international collaborators. The book builds on the previous volume, published in 2022 in the Studies in Computational Intelligence. The current book focuses on the following themes: knowledge discovery with lossless visualizations, AI/ML through visual knowledge discovery with visual analytics case studies application, and visual knowledge discovery in text mining and natural language processing. The intended audience for this collection includes but is not limited to developers of emerging AI/machine learning and visualization applications, scientists, practitioners, and research students. It has multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery, visual analytics, and text and natural language processing. The book provides case examples for future directions in this domain. New researchers find inspiration to join the profession of the field of AI/machine learning through a visualization lens.
Artificial Intelligence For Information Management A Healthcare Perspective
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Author : K. G. Srinivasa
language : en
Publisher: Springer Nature
Release Date : 2021-05-20
Artificial Intelligence For Information Management A Healthcare Perspective written by K. G. Srinivasa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-20 with Technology & Engineering categories.
This book discusses the advancements in artificial intelligent techniques used in the well-being of human healthcare. It details the techniques used in collection, storage and analysis of data and their usage in different healthcare solutions. It also discusses the techniques of predictive analysis in early diagnosis of critical diseases. The edited book is divided into four parts – part A discusses introduction to artificial intelligence and machine learning in healthcare; part B highlights different analytical techniques used in healthcare; part C provides various security and privacy mechanisms used in healthcare; and finally, part D exemplifies different tools used in visualization and data analytics.
Data Visualization
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Author : Margret Anouncia S
language : en
Publisher: Springer
Release Date : 2020-04-01
Data Visualization written by Margret Anouncia S and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-01 with Computers categories.
This book discusses the recent trends and developments in the fields of information processing and information visualization. In view of the increasing amount of data, there is a need to develop visualization techniques to make that data easily understandable. Presenting such approaches from various disciplines, this book serves as a useful resource for graduates.
Interactive Data Visualization For The Web
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Author : Scott Murray
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-03-11
Interactive Data Visualization For The Web written by Scott Murray and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-11 with Computers categories.
Create and publish your own interactive data visualization projects on the Web—even if you have little or no experience with data visualization or web development. It’s easy and fun with this practical, hands-on introduction. Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser. Along the way, you’ll expand your web programming skills, using tools such as HTML and JavaScript. This step-by-step guide is ideal whether you’re a designer or visual artist with no programming experience, a reporter exploring the new frontier of data journalism, or anyone who wants to visualize and share data. Learn HTML, CSS, JavaScript, and SVG basics Dynamically generate web page elements from your data—and choose visual encoding rules to style them Create bar charts, scatter plots, pie charts, stacked bar charts, and force-directed layouts Use smooth, animated transitions to show changes in your data Introduce interactivity to help users explore data through different views Create customized geographic maps with data Explore hands-on with downloadable code and over 100 examples
Data Science Data Visualization And Digital Twins
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Author : Sara Shirowzhan
language : en
Publisher:
Release Date : 2022
Data Science Data Visualization And Digital Twins written by Sara Shirowzhan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Data mining categories.
Visualizing Data
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Author : Ben Fry
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2008
Visualizing Data written by Ben Fry and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
Provides information on the methods of visualizing data on the Web, along with example projects and code.