Machine Learning And The City

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Machine Learning and the City

Author : Silvio Carta
Publisher : John Wiley & Sons
ISBN 13 : 1119749638
Total Pages : 676 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning and the City by : Silvio Carta

Download or read book Machine Learning and the City written by Silvio Carta and published by John Wiley & Sons. This book was released on 2022-05-17 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and the City Explore the applications of machine learning and artificial intelligence to the built environment Machine Learning and the City: Applications in Architecture and Urban Design delivers a robust exploration of machine learning (ML) and artificial intelligence (AI) in the context of the built environment. Relevant contributions from leading scholars in their respective fields describe the ideas and techniques that underpin ML and AI, how to begin using ML and AI in urban design, and the likely impact of ML and AI on the future of city design and planning. Each section couples theoretical and technical chapters, authoritative references, and concrete examples and projects that illustrate the efficacy and power of machine learning in urban design. The book also includes: An introduction to the probabilistic logic that underpins machine learning Comprehensive explorations of the applications of machine learning and artificial intelligence to urban environments Practical discussions of the consequences of applied machine learning and the future of urban design Perfect for designers approaching machine learning and AI for the first time, Machine Learning and the City: Applications in Architecture and Urban Design will also earn a place in the libraries of urban planners and engineers involved in urban design.

Urban Informatics

Author : Wenzhong Shi
Publisher : Springer Nature
ISBN 13 : 9811589836
Total Pages : 941 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Urban Informatics by : Wenzhong Shi

Download or read book Urban Informatics written by Wenzhong Shi and published by Springer Nature. This book was released on 2021-04-06 with total page 941 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.

Artificial Intelligence in Urban Planning and Design

Author : Imdat As
Publisher : Elsevier
ISBN 13 : 0128239425
Total Pages : 404 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Artificial Intelligence in Urban Planning and Design by : Imdat As

Download or read book Artificial Intelligence in Urban Planning and Design written by Imdat As and published by Elsevier. This book was released on 2022-05-14 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Urban Planning and Design: Technologies, Implementation, and Impacts is the most comprehensive resource available on the state of Artificial Intelligence (AI) as it relates to smart city planning and urban design. The book explains nascent applications of AI technologies in urban design and city planning, providing a thorough overview of AI-based solutions. It offers a framework for discussion of theoretical foundations of AI, AI applications in the urban design, AI-based research and information systems, and AI-based generative design systems. The concept of AI generates unprecedented city planning solutions without defined rules in advance, a development raising important questions issues for urban design and city planning. This book articulates current theoretical and practical methods, offering critical views on tools and techniques and suggests future directions for the meaningful use of AI technology. Includes a cutting-edge catalogue of AI tools applied to smart city design and planning Provides case studies from around the globe at various scales Includes diagrams and graphics for course instruction

Smart Cities and Machine Learning in Urban Health

Author : Thomas, J. Joshua
Publisher : IGI Global
ISBN 13 : 1799871789
Total Pages : 269 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Smart Cities and Machine Learning in Urban Health by : Thomas, J. Joshua

Download or read book Smart Cities and Machine Learning in Urban Health written by Thomas, J. Joshua and published by IGI Global. This book was released on 2021-11-12 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: The perception of smart cities encompasses a strategy that uses different types of technologies, artificial intelligence (AI), and machine learning and in which, through the internet of things (IoT) and sensor-based data collection, the strategy extrapolates information using insights gained from that data to manage or monitor or track assets, resources, and services efficiently in an urban area. Both these models deeply affect the localities where they are applied and can create together immense possibilities for urban recovery, better quality of life, physical and mental health protection, and economic and social redevelopment. Smart Cities and Machine Learning in Urban Health promotes interdisciplinary work that develops and illustrates the concept of resilience in relation to smart city and machine learning. The book examines the ability of an area and its communities to recover quickly from difficulties; the rigidness and resistance of an area and its communities to possible crisis; the ability of an area, its communities, infrastructure, and business to spring back into shape; and the responsiveness and mitigation towards the crisis with a special look at the impact of the COVID-19 pandemic. The research’s theoretical foundation rests on a wide range of non-architectural sources, primarily AI, sociology, urban studies, and technological development, but it explores everything on cases taken from real cities, thus transforming them into pieces of architectural interest. Covering topics such as carbon emissions, digital healthcare systems, and urban transformation, this book is an essential resource for graduate and post-graduate students, policymakers, researchers, university faculty, engineers, public management, hospital administration, professors, and academicians.

Introduction to Machine Learning

Author : Ethem Alpaydin
Publisher : MIT Press
ISBN 13 : 0262028182
Total Pages : 639 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Introduction to Machine Learning by : Ethem Alpaydin

Download or read book Introduction to Machine Learning written by Ethem Alpaydin and published by MIT Press. This book was released on 2014-08-22 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.

The Hundred-page Machine Learning Book

Author : Andriy Burkov
Publisher :
ISBN 13 : 9781999579500
Total Pages : 141 pages
Book Rating : 4.5/5 (795 download)

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Book Synopsis The Hundred-page Machine Learning Book by : Andriy Burkov

Download or read book The Hundred-page Machine Learning Book written by Andriy Burkov and published by . This book was released on 2019 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue.

Artificial Intelligence and Machine Learning in Smart City Planning

Author : Vedik Basetti
Publisher : Elsevier
ISBN 13 : 0323995047
Total Pages : 362 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Artificial Intelligence and Machine Learning in Smart City Planning by : Vedik Basetti

Download or read book Artificial Intelligence and Machine Learning in Smart City Planning written by Vedik Basetti and published by Elsevier. This book was released on 2023-01-11 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Machine Learning in Smart City Planning shows the reader practical applications of AIML techniques and describes recent advancements in this area in various sectors. Owing to the multidisciplinary nature, this book primarily focuses on the concepts of AIML and its methodologies such as evolutionary techniques, neural networks, machine learning, deep learning, block chain technology, big data analytics, and image processing in the context of smart cities. The text also discusses possible solutions to different challenges posed by smart cities by presenting cutting edge AIML techniques using different methodologies, as well as future directions for those same techniques. Reviews the smart city concept and teaches how it can contribute to achieving urban development priorities Explains soft computing techniques for smart city applications Describes how to model problems for effective analysis, intelligent decision making, and optimal operation and control in the smart city paradigm Teaches how to carry out independent projects using soft computing techniques in a vast range of areas in diverse fields like engineering, management, and sciences

Deep Learning

Author : Ian Goodfellow
Publisher : MIT Press
ISBN 13 : 0262337371
Total Pages : 801 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Deep Learning by : Ian Goodfellow

Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Deep Learning Illustrated

Author : Jon Krohn
Publisher : Addison-Wesley Professional
ISBN 13 : 0135121728
Total Pages : 725 pages
Book Rating : 4.1/5 (351 download)

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Book Synopsis Deep Learning Illustrated by : Jon Krohn

Download or read book Deep Learning Illustrated written by Jon Krohn and published by Addison-Wesley Professional. This book was released on 2019-08-05 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Machine Intelligence and Data Analytics for Sustainable Future Smart Cities

Author : Uttam Ghosh
Publisher : Springer Nature
ISBN 13 : 3030720659
Total Pages : 411 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Machine Intelligence and Data Analytics for Sustainable Future Smart Cities by : Uttam Ghosh

Download or read book Machine Intelligence and Data Analytics for Sustainable Future Smart Cities written by Uttam Ghosh and published by Springer Nature. This book was released on 2021-05-31 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest advances in computational intelligence and data analytics for sustainable future smart cities. It focuses on computational intelligence and data analytics to bring together the smart city and sustainable city endeavors. It also discusses new models, practical solutions and technological advances related to the development and the transformation of cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.

Machine Learning Proceedings 1995

Author : Machine Learning
Publisher : Morgan Kaufmann
ISBN 13 : 1483298663
Total Pages : 400 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Machine Learning Proceedings 1995 by : Machine Learning

Download or read book Machine Learning Proceedings 1995 written by Machine Learning and published by Morgan Kaufmann. This book was released on 2016-01-22 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Proceedings 1995

Smart Cities and Artificial Intelligence

Author : Christopher Grant Kirwan
Publisher : Elsevier
ISBN 13 : 0128170255
Total Pages : 276 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Smart Cities and Artificial Intelligence by : Christopher Grant Kirwan

Download or read book Smart Cities and Artificial Intelligence written by Christopher Grant Kirwan and published by Elsevier. This book was released on 2020-05-06 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smart Cities and Artificial Intelligence offers a comprehensive view of how cities are evolving as smart ecosystems through the convergence of technologies incorporating machine learning and neural network capabilities, geospatial intelligence, data analytics and visualization, sensors, and smart connected objects. These recent advances in AI move us closer to developing urban operating systems that simulate human, machine, and environmental patterns from transportation infrastructure to communication networks. Exploring cities as real-time, living, dynamic systems, and providing tools and formats including generative design and living lab models that support cities to become self-regulating, this book provides readers with a conceptual and practical knowledge base to grasp and apply the key principles required in the planning, design, and operations of smart cities. Smart Cities and Artificial Intelligence brings a multidisciplinary, integrated approach, examining how the digital and physical worlds are converging, and how a new combination of human and machine intelligence is transforming the experience of the urban environment. It presents a fresh holistic understanding of smart cities through an interconnected stream of theory, planning and design methodologies, system architecture, and the application of smart city functions, with the ultimate purpose of making cities more liveable, sustainable, and self-sufficient. Explores concepts in smart city design and development and the transformation of cities through the convergence of human, machine, and natural systems enabled by Artificial Intelligence (AI) Includes numerous diagrams to illustrate and explain complex smart city systems and solutions Features diverse smart city examples and initiatives from around the globe

The Smart Enough City

Author : Ben Green
Publisher : MIT Press
ISBN 13 : 0262039672
Total Pages : 241 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Smart Enough City by : Ben Green

Download or read book The Smart Enough City written by Ben Green and published by MIT Press. This book was released on 2019-04-07 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why technology is not an end in itself, and how cities can be “smart enough,” using technology to promote democracy and equity. Smart cities, where technology is used to solve every problem, are hailed as futuristic urban utopias. We are promised that apps, algorithms, and artificial intelligence will relieve congestion, restore democracy, prevent crime, and improve public services. In The Smart Enough City, Ben Green warns against seeing the city only through the lens of technology; taking an exclusively technical view of urban life will lead to cities that appear smart but under the surface are rife with injustice and inequality. He proposes instead that cities strive to be “smart enough”: to embrace technology as a powerful tool when used in conjunction with other forms of social change—but not to value technology as an end in itself. In a technology-centric smart city, self-driving cars have the run of downtown and force out pedestrians, civic engagement is limited to requesting services through an app, police use algorithms to justify and perpetuate racist practices, and governments and private companies surveil public space to control behavior. Green describes smart city efforts gone wrong but also smart enough alternatives, attainable with the help of technology but not reducible to technology: a livable city, a democratic city, a just city, a responsible city, and an innovative city. By recognizing the complexity of urban life rather than merely seeing the city as something to optimize, these Smart Enough Cities successfully incorporate technology into a holistic vision of justice and equity.

Art in the Age of Machine Learning

Author : Sofian Audry
Publisher : MIT Press
ISBN 13 : 0262367106
Total Pages : 215 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Art in the Age of Machine Learning by : Sofian Audry

Download or read book Art in the Age of Machine Learning written by Sofian Audry and published by MIT Press. This book was released on 2021-11-23 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: An examination of machine learning art and its practice in new media art and music. Over the past decade, an artistic movement has emerged that draws on machine learning as both inspiration and medium. In this book, transdisciplinary artist-researcher Sofian Audry examines artistic practices at the intersection of machine learning and new media art, providing conceptual tools and historical perspectives for new media artists, musicians, composers, writers, curators, and theorists. Audry looks at works from a broad range of practices, including new media installation, robotic art, visual art, electronic music and sound, and electronic literature, connecting machine learning art to such earlier artistic practices as cybernetics art, artificial life art, and evolutionary art. Machine learning underlies computational systems that are biologically inspired, statistically driven, agent-based networked entities that program themselves. Audry explains the fundamental design of machine learning algorithmic structures in terms accessible to the nonspecialist while framing these technologies within larger historical and conceptual spaces. Audry debunks myths about machine learning art, including the ideas that machine learning can create art without artists and that machine learning will soon bring about superhuman intelligence and creativity. Audry considers learning procedures, describing how artists hijack the training process by playing with evaluative functions; discusses trainable machines and models, explaining how different types of machine learning systems enable different kinds of artistic practices; and reviews the role of data in machine learning art, showing how artists use data as a raw material to steer learning systems and arguing that machine learning allows for novel forms of algorithmic remixes.

Advances in Deep Learning Applications for Smart Cities

Author : Kumar, Rajeev
Publisher : IGI Global
ISBN 13 : 1799897125
Total Pages : 335 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Advances in Deep Learning Applications for Smart Cities by : Kumar, Rajeev

Download or read book Advances in Deep Learning Applications for Smart Cities written by Kumar, Rajeev and published by IGI Global. This book was released on 2022-05-13 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within the past decade, technology has grown exponentially, and governments have promoted smart cities. Emerging smart cities have become both crucibles and showrooms for the practical application of the internet of things (IoT), cloud computing, and the integration of big data into everyday life. This complex concoction requires new thinking of the synergistic utilization of deep learning and blockchain methods and data-driven decision making with automation infrastructure, autonomous transportation, and more. Advances in Deep Learning Applications for Smart Cities provides a global perspective on current and future trends concerning the integration of deep learning and blockchain for smart cities. It provides valuable insights on the best practices and success factors for smart cities. Covering topics such as digital healthcare, object detection methods, and power consumption, this book is an excellent reference for researchers, scientists, libraries, industry experts, government organizations, students and educators of higher education, business professionals, communication and marketing agencies, entrepreneurs, and academicians.

Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities

Author : Panos M. Pardalos
Publisher : Springer Nature
ISBN 13 : 3030844595
Total Pages : 239 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities by : Panos M. Pardalos

Download or read book Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities written by Panos M. Pardalos and published by Springer Nature. This book was released on 2022-01-09 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities. Special features include: New research on the design of city elements and smart systems with respect to new technologies and scientific thinking Discussions on the theoretical background that lead to smart cities for the future New technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environments The book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.

Machine Learning Approaches for Urban Computing

Author : Mainak Bandyopadhyay
Publisher : Springer Nature
ISBN 13 : 9811609357
Total Pages : 208 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Machine Learning Approaches for Urban Computing by : Mainak Bandyopadhyay

Download or read book Machine Learning Approaches for Urban Computing written by Mainak Bandyopadhyay and published by Springer Nature. This book was released on 2021-04-28 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses various machine learning applications and models, developed using heterogeneous data, which helps in a comprehensive prediction, optimization, association analysis, cluster analysis and classification-related applications for various activities in urban area. It details multiple types of data generating from urban activities and suitability of various machine learning algorithms for handling urban data. The book is helpful for researchers, academicians, faculties, scientists and geospatial industry professionals for their research work and sets new ideas in the field of urban computing.