Ethics Machine Learning And Python In Geospatial Analysis
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Ethics Machine Learning And Python In Geospatial Analysis
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Author : Galety, Mohammad Gouse
language : en
Publisher: IGI Global
Release Date : 2024-04-29
Ethics Machine Learning And Python In Geospatial Analysis written by Galety, Mohammad Gouse and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-29 with Technology & Engineering categories.
In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management. Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and machine learning. The book’s meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques.
Ethics Machine Learning And Python In Geospatial Analysis
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Author : Mohammad Gouse Galety
language : en
Publisher:
Release Date : 2024
Ethics Machine Learning And Python In Geospatial Analysis written by Mohammad Gouse Galety and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management. Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and machine learning. The books meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques. Scholars and practitioners can now enhance their analytical capabilities and unlock deeper insights from geospatial data with the guidance of this pivotal book. From manipulating data structures to employing machine learning algorithms, it equips readers with the tools and knowledge to tackle complex geospatial problems confidently and precisely. With Ethics, Machine Learning, and Python in Geospatial Analysis , the era of cumbersome manual processes gives way to a new frontier of efficient, data-driven analysis, empowering scholars to make meaningful contributions to geospatial science.
Generative Ai Foundations Developments And Applications
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Author : Kannan, Rajkumar
language : en
Publisher: IGI Global
Release Date : 2025-03-26
Generative Ai Foundations Developments And Applications written by Kannan, Rajkumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-26 with Computers categories.
In recent years, the field of generative artificial intelligence (AI) has witnessed remarkable advancements, transforming various domains from art and music to language and healthcare. Advanced techniques, such as conditional generation, style transfer, and unsupervised learning, showcase the cutting-edge research shaping the field. The ability of generative AI models to create novel content autonomously has sparked immense interest and innovation. Future directions provide speculations for potential breakthroughs, challenges, and opportunities for further research and innovation. Generative AI Foundations, Developments, and Applications serves as a resource to understanding generative AI across various domains including natural language processing, computer vision, and drug discovery. It explores the theoretical foundations, latest developments, and practical applications of generative AI. Covering topics such as prompt engineering, multimodal data fusion, and natural language processing, this book is an excellent resource for computer scientists, computer engineers, practitioners, professionals, researchers, scholars, academicians, and more.
Data Analytics And Ai For Quantitative Risk Assessment And Financial Computation
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Author : Galety, Mohammad Gouse
language : en
Publisher: IGI Global
Release Date : 2024-11-29
Data Analytics And Ai For Quantitative Risk Assessment And Financial Computation written by Galety, Mohammad Gouse and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Business & Economics categories.
In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape.
Developing Kaggle Notebooks
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Author : Gabriel Preda
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-27
Developing Kaggle Notebooks written by Gabriel Preda 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 2023-12-27 with Computers categories.
Printed in Color Develop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Notebooks with substance, style and impact Leverage the power of Generative AI with Kaggle Models Purchase of the print or Kindle book includes a free PDF eBook Key Features Master the basics of data ingestion, cleaning, exploration, and prepare to build baseline models Work robustly with any type, modality, and size of data, be it tabular, text, image, video, or sound Improve the style and readability of your Notebooks, making them more impactful and compelling Book DescriptionDeveloping Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques. For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable. Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.What you will learn Approach a dataset or competition to perform data analysis via a notebook Learn data ingestion and address issues arising with the ingested data Structure your code using reusable components Analyze in depth both small and large datasets of various types Distinguish yourself from the crowd with the content of your analysis Enhance your notebook style with a color scheme and other visual effects Captivate your audience with data and compelling storytelling techniques Who this book is for This book is suitable for a wide audience with a keen interest in data science and machine learning, looking to use Kaggle Notebooks to improve their skills and rise in the Kaggle Notebooks ranks. This book caters to: Beginners on Kaggle from any background Seasoned contributors who want to build various skills like ingestion, preparation, exploration, and visualization Expert contributors who want to learn from the Grandmasters to rise into the upper Kaggle rankings Professionals who already use Kaggle for learning and competing
Fast And Practical Gis
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-05-03
Fast And Practical Gis 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 2025-05-03 with Computers categories.
**Fast and Practical GIS** provides a comprehensive introduction to Geographic Information Systems (GIS), covering the basics of GIS software, data management, spatial analysis, and GIS applications. This book is designed for students, professionals, and anyone who wants to learn more about GIS. With clear and concise explanations and practical examples, this book will help you: * Understand the basics of GIS and how it can be used to solve real-world problems * Learn how to use GIS software to create maps, perform spatial analysis, and develop GIS applications * Explore emerging trends in GIS, such as cloud computing, mobile GIS, and big data This book is packed with practical examples and exercises that will help you learn how to use GIS effectively. You will also find case studies that show how GIS is being used to solve real-world problems in a variety of fields, including: * Urban planning * Environmental management * Public health * Business and marketing * Transportation and logistics Whether you are new to GIS or you are looking to expand your knowledge, this book is the perfect resource. With Fast and Practical GIS, you will be able to use GIS to make better decisions and improve your understanding of the world around you. **What's Inside:** * An introduction to GIS and its benefits * A guide to GIS software and data management * A tutorial on spatial analysis techniques * A discussion of GIS applications in a variety of fields * A look at emerging trends in GIS **About the Author:** Pasquale De Marco is a GIS professional with over 10 years of experience. He has worked on a variety of GIS projects, including urban planning, environmental management, and public health. He is also a certified GIS instructor. If you like this book, write a review on google books!
Explainable Machine Learning For Geospatial Data Analysis
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Author : Courage Kamusoko
language : en
Publisher: CRC Press
Release Date : 2024-12-06
Explainable Machine Learning For Geospatial Data Analysis written by Courage Kamusoko and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-06 with Technology & Engineering categories.
Explainable machine learning (XML), a subfield of AI, is focused on making complex AI models understandable to humans. This book highlights and explains the details of machine learning models used in geospatial data analysis. It demonstrates the need for a data-centric, explainable machine learning approach to obtain new insights from geospatial data. It presents the opportunities, challenges, and gaps in the machine and deep learning approaches for geospatial data analysis and how they are applied to solve various environmental problems in land cover changes and in modeling forest canopy height and aboveground biomass density. The author also includes guidelines and code scripts (R, Python) valuable for practical readers. Features Data-centric explainable machine learning (ML) approaches for geospatial data analysis. The foundations and approaches to explainable ML and deep learning. Several case studies from urban land cover and forestry where existing explainable machine learning methods are applied. Descriptions of the opportunities, challenges, and gaps in data-centric explainable ML approaches for geospatial data analysis. Scripts in R and python to perform geospatial data analysis, available upon request. This book is an essential resource for graduate students, researchers, and academics working in and studying data science and machine learning, as well as geospatial data science professionals using GIS and remote sensing in environmental fields.
Handbook Of Geospatial Artificial Intelligence
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Author : Song Gao
language : en
Publisher: CRC Press
Release Date : 2023-12-29
Handbook Of Geospatial Artificial Intelligence written by Song Gao and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-29 with Technology & Engineering categories.
This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), which is the integration of geospatial studies and AI machine (deep) learning and knowledge graph technologies. It explains key fundamental concepts, methods, models, and technologies of GeoAI, and discusses the recent advances, research tools, and applications that range from environmental observation and social sensing to natural disaster responses. As the first single volume on this fast-emerging domain, Handbook of Geospatial Artificial Intelligence is an excellent resource for educators, students, researchers, and practitioners utilizing GeoAI in fields such as information science, environment and natural resources, geosciences, and geography. Features Provides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectives Covers a wide range of GeoAI applications and case studies in practice Offers supplementary materials such as data, programming code, tools, and case studies Discusses the recent developments of GeoAI methods and tools Includes contributions written by top experts in cutting-edge GeoAI topics This book is intended for upper-level undergraduate and graduate students from different disciplines and those taking GIS courses in geography or computer sciences as well as software engineers, geospatial industry engineers, GIS professionals in non-governmental organizations, and federal/state agencies who use GIS and want to learn more about GeoAI advances and applications.
The Routledge International Handbook Of Universities Security And Intelligence Studies
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Author : Liam Gearon
language : en
Publisher: Routledge
Release Date : 2019-10-08
The Routledge International Handbook Of Universities Security And Intelligence Studies written by Liam Gearon and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-08 with Education categories.
In an era of intensified international terror, universities have been increasingly drawn into an arena of locating, monitoring and preventing such threats, forcing them into often covert relationships with the security and intelligence agencies. With case studies from across the world, the Routledge International Handbook of Universities, Security and Intelligence Studies provides a comparative, in-depth analysis of the historical and contemporary relationships between global universities, national security and intelligence agencies. Written by leading international experts and from multidisciplinary perspectives, the Routledge International Handbook of Universities, Security and Intelligence Studies provides theoretical, methodological and empirical definition to academic, scholarly and research enquiry at the interface of higher education, security and intelligence studies. Divided into eight sections, the Handbook explores themes such as: the intellectual frame for our understanding of the university-security-intelligence network; historical, contemporary and future-looking interactions from across the globe; accounts of individuals who represent the broader landscape between universities and the security and intelligence agencies; the reciprocal interplay of personnel from universities to the security and intelligence agencies and vice versa; the practical goals of scholarship, research and teaching of security and intelligence both from within universities and the agencies themselves; terrorism research as an important dimension of security and intelligence within and beyond universities; the implication of security and intelligence in diplomacy, journalism and as an element of public policy; the extent to which security and intelligence practice, research and study far exceeds the traditional remit of commonly held notions of security and intelligence. Bringing together a unique blend of leading academic and practitioner authorities on security and intelligence, the Routledge International Handbook of Universities, Security and Intelligence Studies is an essential and authoritative guide for researchers and policymakers looking to understand the relationship between universities, the security services and the intelligence community.
Applied Geospatial Data Science With Python
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Author : David S. Jordan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-02-28
Applied Geospatial Data Science With Python written by David S. Jordan 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 2023-02-28 with Computers categories.
Intelligently connect data points and gain a deeper understanding of environmental problems through hands-on Geospatial Data Science case studies written in Python The book includes colored images of important concepts Key Features Learn how to integrate spatial data and spatial thinking into traditional data science workflows Develop a spatial perspective and learn to avoid common pitfalls along the way Gain expertise through practical case studies applicable in a variety of industries with code samples that can be reproduced and expanded Book DescriptionData scientists, when presented with a myriad of data, can often lose sight of how to present geospatial analyses in a meaningful way so that it makes sense to everyone. Using Python to visualize data helps stakeholders in less technical roles to understand the problem and seek solutions. The goal of this book is to help data scientists and GIS professionals learn and implement geospatial data science workflows using Python. Throughout this book, you’ll uncover numerous geospatial Python libraries with which you can develop end-to-end spatial data science workflows. You’ll learn how to read, process, and manipulate spatial data effectively. With data in hand, you’ll move on to crafting spatial data visualizations to better understand and tell the story of your data through static and dynamic mapping applications. As you progress through the book, you’ll find yourself developing geospatial AI and ML models focused on clustering, regression, and optimization. The use cases can be leveraged as building blocks for more advanced work in a variety of industries. By the end of the book, you’ll be able to tackle random data, find meaningful correlations, and make geospatial data models.What you will learn Understand the fundamentals needed to work with geospatial data Transition from tabular to geo-enabled data in your workflows Develop an introductory portfolio of spatial data science work using Python Gain hands-on skills with case studies relevant to different industries Discover best practices focusing on geospatial data to bring a positive change in your environment Explore solving use cases, such as traveling salesperson and vehicle routing problems Who this book is for This book is for you if you are a data scientist seeking to incorporate geospatial thinking into your workflows or a GIS professional seeking to incorporate data science methods into yours. You’ll need to have a foundational knowledge of Python for data analysis and/or data science.