Modern Artificial Intelligence And Data Science 2024
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Modern Artificial Intelligence And Data Science 2024
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Author : Abdellah Idrissi
language : en
Publisher: Springer Nature
Release Date : 2024-10-03
Modern Artificial Intelligence And Data Science 2024 written by Abdellah Idrissi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-03 with Computers categories.
This book, through its various chapters presenting recent advances in Modern Artificial Intelligence and Data Science as well as their applications, aims to set up lasting and real applications necessary for both academics and professionals. By its proposals of new ideas, it serves as a real guide both to informed readers and to beginners in these specialized fields. It also covers applications that discuss how they can support societal challenges such as education, health, agriculture, clean energy, business, environment, and security. Readers will find here the fruit of many research ideas covering a wide range of application areas that can be explored for the advancement of their research or the development of their business. These ideas present new techniques and trends projected in various areas of daily life. This book is therefore intended for Designers, Developers, Decision-Makers, Consultants, Engineers, and of course Master's/Doctorate Students, Researchers, and Universities.
Artificial Intelligence With Python
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Author : Prateek Joshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-01-27
Artificial Intelligence With Python written by Prateek Joshi 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 2017-01-27 with Computers categories.
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
Handbook Of Research On Applied Data Science And Artificial Intelligence In Business And Industry
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Author : Chkoniya, Valentina
language : en
Publisher: IGI Global
Release Date : 2021-06-25
Handbook Of Research On Applied Data Science And Artificial Intelligence In Business And Industry written by Chkoniya, Valentina and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Computers categories.
The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.
Modern Artificial Intelligence And Data Science
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Author : Abdellah Idrissi
language : en
Publisher: Springer Nature
Release Date : 2023-08-25
Modern Artificial Intelligence And Data Science written by Abdellah Idrissi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-25 with Computers categories.
This Book, through its various chapters presenting the Recent Advances in Modern Artificial Intelligence and Data Science as well as their Applications, aims to set up lasting and real applications necessary for both academics and professionals. Readers find here the fruit of many research ideas covering a wide range of application areas that can be explored for the advancement of their research or the development of their business. These ideas present new techniques and trends projected in various areas of daily life. Through its proposals of new ideas, this Book serves as a real guide both for experienced readers and for beginners in these specialized fields. It also covers several applications that explain how they can support some societal challenges such as education, health, agriculture, clean energy, business, environment, security and many more. This Book is therefore intended for Designers, Developers, Decision-Makers, Consultants, Engineers, and of course Master's/Doctoral Students, Researchers and Academics.
Encyclopedia Of Data Science And Machine Learning
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Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2023-01-20
Encyclopedia Of Data Science And Machine Learning written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Computers categories.
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Artificial Intelligence And Data Science In Environmental Sensing
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Author : Mohsen Asadnia
language : en
Publisher: Academic Press
Release Date : 2022-02-09
Artificial Intelligence And Data Science In Environmental Sensing written by Mohsen Asadnia and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-09 with Computers categories.
Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. - Presents tools, connections and proactive solutions to take sustainability programs to the next level - Offers a practical guide for making students proficient in modern electronic data analysis and graphics - Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery
Modern Artificial Intelligence Based On Soft Computing Techniques
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Author : Patricia Melin
language : en
Publisher: Springer Nature
Release Date : 2025-07-05
Modern Artificial Intelligence Based On Soft Computing Techniques written by Patricia Melin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-05 with Computers categories.
This book describes what we can call modern artificial intelligence that includes the theoretical developments and applications of soft computing techniques. Soft computing includes fuzzy logic, neural networks and meta-heuristic algorithms, as well as their hybrid combinations. There are papers with the main topics from type-1 to type-3 fuzzy logic, which basically consists of a group of papers that propose new concepts and algorithms based on type-1, type-2 and type-3 fuzzy logic and their applications. There are also papers that present theory and practice of meta-heuristics in diverse application areas. There are interesting papers on different applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. In addition, we can find papers describing applications of fuzzy logic, neural networks and meta-heuristics in robotics problems.
Emerging Artificial Intelligence Applications In Computer Engineering
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Author : Ilias G. Maglogiannis
language : en
Publisher: IOS Press
Release Date : 2007
Emerging Artificial Intelligence Applications In Computer Engineering written by Ilias G. Maglogiannis and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
Provides insights on how computer engineers can implement artificial intelligence (AI) in real world applications. This book presents practical applications of AI.
Choosing Chinese Universities
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Author : Alice Y.C. Te
language : en
Publisher: Routledge
Release Date : 2022-10-07
Choosing Chinese Universities written by Alice Y.C. Te and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-07 with Education categories.
This book unpacks the complex dynamics of Hong Kong students’ choice in pursuing undergraduate education at the universities of Mainland China. Drawing on an empirical study based on interviews with 51 students, this book investigates how macro political/economic factors, institutional influences, parental influence, and students’ personal motivations have shaped students’ eventual choice of university. Building on Perna’s integrated model of college choice and Lee’s push-pull mobility model, this book conceptualizes that students’ border crossing from Hong Kong to Mainland China for higher education is a trans-contextualized negotiated choice under the "One Country, Two Systems" principle. The findings reveal that during the decision-making process, influencing factors have conditioned four archetypes of student choice: Pragmatists, Achievers, Averages, and Underachievers. The book closes by proposing an enhanced integrated model of college choice that encompasses both rational motives and sociological factors, and examines the theoretical significance and practical implications of the qualitative study. With its focus on student choice and experiences of studying in China, this book’s research and policy findings will interest researchers, university administrators, school principals, and teachers.
Artificial Intelligence Implementation In Education Processes
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Author : Dina Darwish
language : en
Publisher: Deep Science Publishing
Release Date : 2025-02-09
Artificial Intelligence Implementation In Education Processes written by Dina Darwish and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-09 with Computers categories.
Currently, numerous issues for enhancing teaching and learning remain unaddressed. Educators pursue technology-driven methods that are secure, efficient, and scalable to meet these aims. Educators naturally question whether the swift technological advancements in daily life could be beneficial. Similar to everyone else, educators utilise AI-driven services in their daily routines, including voice assistants in their residences, tools for grammar correction, sentence completion, and essay writing, as well as automated travel planning applications on their mobile devices. A multitude of educators is currently investigating freshly emerging AI tools. Educators recognise the potential of AI-driven technologies, such as speech recognition, to enhance support for students with disabilities, multilingual learners, and others who could gain from increased adaptability and personalisation in educational digital tools. They are investigating how AI can facilitate the composition or enhancement of lessons, along with their methodology for sourcing, selecting, and modifying materials for instructional usage. Educators are cognisant of emerging threats. Beneficial and potent functionalities may potentially provide novel data privacy and security vulnerabilities. Educators acknowledge that AI can autonomously generate output that is unsuitable or erroneous. They are apprehensive that the associations or automations generated by AI may exacerbate undesirable biases. Although it appeared to have appeared out of nowhere, artificial intelligence (AI) was really created over a period of many years, just like so many other technologies that have had a significant impact on the world. In today's world, artificial intelligence is pervasive and has the potential to revolutionize education. By employing AI, educators are able to personalize learning experiences to meet the specific requirements of each student, so making education more efficient and interesting. In addition, technologies that are enabled by artificial intelligence help with administrative work, which streamlines operations and frees up teachers to concentrate on teaching. Educators and school administrators are currently utilizing tools driven by artificial intelligence, and applications dependent on AI in the field of education. The benefits of AI in education include fostering innovation, condensing current materials, among others. The following section will explore the advantages and disadvantages of AI in educational institutions, emphasising its potential to transform the learning environment. Here is a concise overview of some benefits of using AI in education. - It can be utilised to customise education. AI can assist in customising content to meet the specific needs and learning styles of individual students, utilising AI-driven analytics that provide insights into student performance and learning trends. Thus, AI enhances student engagement and motivation. - It can furnish students with prompt feedback. AI provides students with immediate and comprehensive feedback on their assignments, enabling them to identify their strengths and faults. This feedback improves comprehension and educational results, guiding teachers on future course priorities. - It can be utilised to generate and enhance content. AI-powered platforms enable the creation of lessons, activities, evaluations, discussion prompts, and presentations by inputting a brief prompt including keywords. - It may yield more inclusive instruction. AI possesses robust technologies that provide previously unattainable resources accessible to students with unique needs. Technological tools providing text-to-speech, visual recognition, speech recognition, and additional functionalities can assist educators in modifying resources to ensure equitable learning opportunities for all students. - It can facilitate enhanced access to resources. Educators can utilise numerous AI-driven tools to improve and augment classroom learning. Examples include Canva Magic Write, which assists in brainstorming, outlining, and lesson planning; Curipod, which allows educators to swiftly develop interactive lessons; Eduaide, offering over 100 resource types for the creation of high-quality instructional materials; and Quizzizz, utilised for designing quizzes that generate personalised learning pathways based on individual student responses. - It can enhance the comprehensibility of abstract concepts. Image-generating AI systems like Picsart and Visme can transform intricate concepts into more accessible content. - It can be utilised to manage administrative responsibilities. AI can be utilised to optimise administrative functions including grading, scheduling, parent communication, and student record management. This enables educators to focus on your primary expertise; teaching. It provides increased direct engagement with kids and ensures that no individual is overlooked. - It can cultivate critical thinking. The emergence and increasing application of AI in educational settings prompts discussions about critical thinking and ethical implications. Students exhibit a natural curiosity in AI. The profound talks may aid in their growth and development as thinkers and learners. The Obstacles and Constraints of Artificial Intelligence in Education Despite the numerous benefits that AI presents to educators, learners, and administrators, it also poses certain obstacles and disadvantages. The subsequent list enumerates prevalent concerns that affect educators. - Concerns Regarding Privacy and Security. Privacy hazards have been a worry since the inception of AI. Individuals are apprehensive regarding the collection and utilisation of their personal data, as well as their awareness and control over its application. Numerous individuals express apprehensions over the security of their data storage and its protection against potential breaches. Additional concerns encompass the exposure of private and sensitive information to unauthorised individuals, the propagation of incorrect or misleading information, and the growing accessibility of personal data by others. Generally, dangers are associated with data collecting, data processing, data distribution, and intrusion into an individual's personal space, choices, or actions. - Possible Bias in AI Algorithms. Research indicates considerable bias in GPT (generative pre-trained transformers; e.g., ChatGPT) towards non-native English speakers. One study indicates that more than fifty percent of non-native English writing samples were erroneously categorised as AI-generated, but the classification accuracy for native English speakers was practically flawless. A contributing factor to the issue is that GPT detectors are designed to identify text that is more literary and intricate as being more "human." Consequently, authors who do not employ such terminology are more prone to being classified as utilising AI-generated content and may be unfairly marked for AI plagiarism. Students who do not speak English may be unjustly accused of academic dishonesty, thus jeopardising their educational trajectory and harming their mental well-being. In evaluating non-native English speakers, it is advisable to refrain from utilising GPT detectors as assessment instruments until these detectors undergo a more thorough study. They can be utilised more securely as educational tools, assisting students in enhancing their writing skills. - Decreased Human Engagement. Increasing dependence on AI may diminish teacher-student interactions and connections, so undermining the social-emotional dimensions of learning. If those encounters decline, pupils' social skills and interpersonal development would be adversely affected. Educators must recognise and address the social and emotional needs of their students. Conversely, automating administrative activities like lesson planning, grading, and managing student data should liberate instructors' time, allowing them to cultivate relationships with students and enhance their social and emotional development. This practice has demonstrated numerous advantages, such as improved academic performance and increased college enrolment rates. A recent survey indicated that merely 22 percent of students—an unprecedented low—believe their professors endeavour to comprehend their lives beyond the classroom. Educational institutions can leverage AI to enhance the interactions between educators and learners; but, they must exert deliberate effort to do this. It is a critical aspect to monitor and manage well. - Significant Implementation Expenses. The expense of AI in education might significantly fluctuate based on the intended applications by educational institutions. Basic generative AI systems for lesson preparation can be as inexpensive as $25 per month, whereas more extensive adaptive learning systems may cost tens of thousands of dollars. Implementing these extensive systems is similarly costly and exceeds the resources of numerous schools, particularly those in underprivileged neighbourhoods. Additionally, there are continuous expenses associated with system maintenance, updates, and staff training for effective utilisation. - Scholarly Malfeasance. Cheating and plagiarism are, as noted, primary worries with AI expressed by educators. The utilisation of AI for completing assignments, examinations, or composing papers is inequitable to students who adhere to academic integrity, and it diminishes the educational experience for those who engage in dishonest practices. If students resort to cheating and shortcuts in their education, what type of citizens will they become upon completion of their studies? Protocols must be established to guarantee that AI is not employed unethically. - Uncertainty and Erroneous Data. Artificial intelligence is contingent upon the quality of its underlying algorithms. If the underlying data is flawed or prejudiced, the resultant information will also be flawed or prejudiced. Students must have the ability to assess and critically analyse the material they encounter rather than merely accepting it at face value. A plethora of instructional resources is available online to assist them in their endeavour. Generative AI provides educators, learners, and administrators with potent tools that can be effectively utilised in the educational sector. Comprehending the advantages and disadvantages of artificial intelligence in education is essential for the proper utilisation of these tools. Investigating the impact of AI on education, both advantageous and detrimental, assists administrators in formulating policies that improve student learning while mitigating possible disadvantages. It can optimise administrative duties, allowing teachers to allocate more time to foster relationships and enhance students' social and emotional skills, customise learning experiences based on individual needs and learning styles, and enhance accessibility for students with disabilities. It assists researchers in gathering and analysing data to improve curriculum efficacy and identify areas for enhancement, while providing a diverse array of educational tools and platforms for students and educators alike. However, it also has its drawbacks. Issues regarding AI in education encompass privacy and security concerns, algorithmic bias that may influence educational results, the risk of excessive dependence on technology detracting from teacher-student interactions, and the financial implications of deploying and sustaining AI technologies in educational institutions. Moreover, technology may be employed unethically in the absence of robust protections and monitoring systems, and its information is only as comprehensive and precisely representative as its algorithms permit. Educators and administrators must evaluate the advantages and disadvantages of AI in education as they consider its application for themselves and their pupils. By evaluating the advantages and disadvantages of AI in the classroom, educators can guarantee that AI's incorporation facilitates significant learning experiences. This book gives a solid foundation on using AI in education for people interested in knowing more information about this topic, and discusses several topics related to using AI in education.