Search results for "Artificial Intelligence and Machine Learning"
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Python & AI For Dummies
Unlock the combined power of Python and AI to supercharge your next technical project and your career Python & AI For Dummies explores the exciting combo of two revolutionary technologies that are reshaping how we work, code, and solve problems. Authors John C. Shovic and Mary Everett draw on their extensive work in computer science, precision agriculture, and artificial intelligence to walk you through the intersection of Python programming and AI applications. No matter your professional background, learn how to use Python's versatility to unlock AI's transformative power. This guide offers hands-on approaches to implementing AI with Python. It moves from foundational concepts to advanced applications, covering essential Python libraries: TensorFlow, PyTorch, OpenCV, and scikit-learn. It also explores essential AI concepts, like neural networks, machine learning models, and natural language processing. Python & AI For Dummies is packed with hands-on projects and real-world examples, that explain how to build machine vision systems, create language models, implement reinforcement learning, and develop AI agents. Broken down into manageable, jargon-free lessons, explore topics from theoretical programming fundamentals to cutting-edge AI applications. Inside the book: Grasp fundamental AI concepts including machine learning, neural networks, and deep learning architecturesExplore eight essential Python libraries designed specifically for AI development and data manipulationBuild practical projects, including machine vision systems, large language models, and AI agentsLearn proven techniques for data preprocessing, model training, and avoiding common pitfalls like overfittingGain insights into emerging technologies including generative AI, transformers, and the Model Context Protocol A can’t-miss resource for programmers interested in expanding their AI skillset, professionals in finance or marketing who want to develop new capabilities, and small business owners ready to streamline their operations, Python & AI For Dummies offers step-by-step guidance, troubleshooting tips, and real-world applications in industries from manufacturing to agriculture.
R 750.00
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Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning
COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligenceAn exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based management, and network virtualization-based managementDiscussions of AI and ML for architectures and frameworks, including cloud systems, software defined networks, 5G and 6G networks, and Edge/Fog networksAn examination of AI and ML for service management, including the automatic generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management.
R 4,753.00
Artificial Intelligence and Machine Learning Techniques for Civil Engineering
In recent years, artificial intelligence (AI) has drawn significant attention with respect to its applications in several scientific fields, varying from big data handling to medical diagnosis. A tremendous transformation has taken place with the emerging application of AI. AI can provide a wide range of solutions to address many challenges in civil engineering. Artificial Intelligence and Machine Learning Techniques for Civil Engineering highlights the latest technologies and applications of AI in structural engineering, transportation engineering, geotechnical engineering, and more. It features a collection of innovative research on the methods and implementation of AI and machine learning in multiple facets of civil engineering. Covering topics such as damage inspection, safety risk management, and information modeling, this premier reference source is an essential resource for engineers, government officials, business leaders and executives, construction managers, students and faculty of higher education, librarians, researchers, and academicians.
R 9,679.66
Machine Learning and AI with Simple Python and Matlab Scripts
A practical guide to AI applications for Simple Python and Matlab scripts Machine Learning and AI with Simple Python and Matlab Scripts: Courseware for Non-computing Majors introduces basic concepts and principles of machine learning and artificial intelligence to help readers develop skills applicable to many popular topics in engineering and science. Step-by-step instructions for simple Python and Matlab scripts mimicking real-life applications will enter the readers into the magical world of AI, without requiring them to have advanced math and computational skills. The book is supported by instructor only lecture slides and sample exams with multiple-choice questions. Machine Learning and AI with Simple Python and Matlab Scripts includes information on: Artificial neural networks applied to real-world problems such as algorithmic trading of financial assets, Alzheimer’s disease prognosisConvolution neural networks for speech recognition and optical character recognitionRecurrent neural networks for chatbots and natural language translatorsTypical AI tasks including flight control for autonomous drones, dietary menu planning, and route planningAdvanced AI tasks including particle swarm optimization and differential and grammatical evolution as well as the current state of the art in AI tools Machine Learning and AI with Simple Python and Matlab Scripts is an accessible, thorough, and practical learning resource for undergraduate and graduate students in engineering and science programs along with professionals in related industries seeking to expand their skill sets.
R 3,224.00
Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing
Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management.Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology.This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems.This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning.FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field
R 2,984.74
Advances and Trends in Artificial Intelligence. Theory and Applications
This book constitutes the refereed proceedings of the 39th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems on Advances and Trends in Artificial Intelligence, IEA/AIE 2026, held in Kuala Lumpur, Malaysia, July 6–8, 2026.The 99 full papers and 8 short papers included in this book were carefully reviewed and selected from 210 submissions. They focus on the following topical sections: Industry, Manufacturing and Fault Diagnosis; Security, Privacy and Trustworthy AI; Reinforcement and Multi-Agent Learning; Machine Learning Methods and Evaluation; Adaptive Learning and Contrastive/Energy-Based Methods; Fuzzy Systems, Optimization and Emerging Applications.
R 2,233.40
R 6,718.78
Why Machines Learn
'An invaluable companion for anyone who wants a deep understanding of what’s under the hood of often inscrutable machines' Melanie Mitchell A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligenceMachine-learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumour is cancerous, or deciding whether someone gets bail. They now influence discoveries in chemistry, biology and physics - the study of genomes, extra-solar planets, even the intricacies of quantum systems.We are living through a revolution in artificial intelligence that is not slowing down. This major shift is based on simple mathematics, some of which goes back centuries: linear algebra and calculus, the stuff of eighteenth-century mathematics. Indeed by the mid-1850s, a lot of the groundwork was all done. It took the development of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see all around us today. In this enlightening book, Anil Ananthaswamy explains the fundamental maths behind AI, which suggests that the basics of natural and artificial intelligence might follow the same mathematical rules.As Ananthaswamy resonantly concludes, to make the most of our most wondrous technologies we need to understand their profound limitations - the clues lie in the maths that makes AI possible.
R 680.00
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach provides a comprehensive guide for public health authorities, researchers and health professionals in psychological health. The book takes a unique approach by exploring how Artificial Intelligence (AI) and Machine Learning (ML) based solutions can assist with monitoring, detection and intervention for mental health at an early stage. Chapters include computational approaches, computational models, machine learning based anxiety and depression detection and artificial intelligence detection of mental health. With the increase in number of natural disasters and the ongoing pandemic, people are experiencing uncertainty, leading to fear, anxiety and depression, hence this is a timely resource on the latest updates in the field.
R 4,414.00
Artificial Intelligence and Machine Learning Powered Public Service Delivery in Estonia
This book gives a comprehensive overview of the state of Artificial Intelligence (AI), especially machine learning (ML) applications in public service delivery in Estonia, discussing the manifold ethical and legal issues that arise under both European and Estonian law. Final conclusions and recommendations set out and analyze various policy options for the public sector, taking into account recent developments at the European level – such as the AIA proposal – as well as the experience of countries that have issued principles and guidelines or even laws for the use of ML in the public sector. “For two reasons, this study is relevant not only for an audience which is interested in Estonian administrative law. First, the authors base their legal analysis primarily on EU law and provide a state of the art-analysis of the relevant secondary legislation. This makes the book a reference text for the European debate on public sector AI governance. Second, this study is part of a larger research project in which four specific use cases of public sector AI have been developed and tested. The practical insights gained in these projects have provided the authors with an excellent understanding of the opportunities and risks of the technology, which distinguishes this legal analysis from similar enterprises.” Excerpt from the foreword by Professor Thomas Wischmeyer (University of Bielefeld)
R 2,739.61
R 1,069.00
Artificial Intelligence, Learning and Computation in Economics and Finance
This book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, computer science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded.Theoretical and empirical studies featured in this book draw on a variety of approaches such as agent-based modeling, numerical simulations, computable economics, as well as employing tools from artificial intelligence and machine learning algorithms. The use of computational approaches to perform counterfactual thought experiments are also introduced, which help transcend the limits posed by traditional mathematical and statistical tools.The book also includes discussions on methodology, epistemology, history and issues concerning prediction, validation, and inference, all of which have become pertinent with the increasing use of computational approaches in economic analysis.
R 7,294.12
Artificial Intelligence
From humble evolutions in research papers and labs, artificial intelligence (AI)—which encompasses Machine Learning (ML) and Deep Learning (DL)—has matured in its many forms, infused in applications that can learn on their own and become progressively smarter with each interaction and transaction. Coupled with immense stores of data, maturity in CPU and GPU hardware, the invention of new, open source deep learning algorithms, and cloud technologies, operational AI has become available to the masses, setting the wheels in motion for a worldwide AI revolution that has never been seen before. This book attempts to help the reader on their AI journey by covering the concepts of AI, Machine Learning, and Deep Learning in its many forms; key ML and DL algorithms data scientists should learn; ethical challenges for the use of AI; how AI is being used across industries; possible future outlook for AI, and an AI Ladder to help accelerate the AI journey.
R 555.67
R 336.00
Artificial Intelligence and Scientific Method
Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy.Taking a clear, non-technical approach, Donald Gillies focuses on two key topics within AI: machine learning in the Turing tradition and the development of logic programming and its connection with non-monotonic logic. Demonstrating how current views on scientific method are challenged by this recent research, he goes on to suggest a new framework for the study of logic. Finally, Professor Gillies draws on work by such seminal thinkers as Bacon, Gödel, Popper, Penrose, and Lucas toaddress the hotly contested question of whether computers might become intellectually superior to human beings.
R 1,701.00
Machine Learning and Computer Vision for Renewable Energy
As the world grapples with the urgent need for sustainable energy solutions, the limitations of traditional approaches to renewable energy forecasting become increasingly evident. The demand for more accurate predictions in net load forecasting, line loss predictions, and the seamless integration of hybrid solar and battery storage systems is more critical than ever. In response to this challenge, advanced Artificial Intelligence (AI) techniques are emerging as a solution, promising to revolutionize the renewable energy landscape. Machine Learning and Computer Vision for Renewable Energy presents a deep exploration of AI modeling, analysis, performance prediction, and control approaches dedicated to overcoming the pressing issues in renewable energy systems. Transitioning from the complexities of energy prediction to the promise of advanced technology, the book sets its sights on the game-changing potential of computer vision (CV) in the realm of renewable energy. Amidst the struggle to enhance sustainability across industries, CV technology emerges as a powerful ally, collecting invaluable data from digital photos and videos. This data proves instrumental in achieving better energy management, predicting factors affecting renewable energy, and optimizing overall sustainability. Readers, including researchers, academicians, and students, will find themselves immersed in a comprehensive understanding of the AI approaches and CV methodologies that hold the key to resolving the challenges faced by renewable energy systems. Machine Learning and Computer Vision for Renewable Energy positions itself as a catalyst for this change. The book not only addresses the immediate concerns of the energy sector but also details how to achieve a more sustainable future. By emphasizing breakthroughs in CV and AI, the objective is clear: to drive societal progress through research, innovation, and technological advancements in the domain of renewable energy. Academic researchers, professors, college students, and business professionals focused on the intersection of digital transformation and renewable energy will find this book to be an indispensable guide to navigating the challenges and opportunities that lie ahead. With a diverse array of recommended topics, this book stands as a testament to the evolving landscape of AI and computer vision, shaping a sustainable energy future for generations to come.
R 11,382.83
Handbook of Research on Artificial Intelligence and Soft Computing Techniques in Personalized Healthcare Services
This volume demonstrates the diverse state-of-the-art applications that combine artificial intelligence with soft computing, which has great potential for creating smart personalized healthcare services. The book showcases the myriad uses of AI and computer techniques in healthcare that employ deep learning, robotics, machine learning, blockchain, emerging cloud, edge computing, Practical Byzantine Fault Tolerance consensus, CNN architecture, Splunk, genetic algorithms (GA), DurBhashan, and many more. These technologies can be used in healthcare for enhanced data sharing, remote health monitoring, tele-rehabilitation, connecting rural populations with healthcare services, identifying diseases and health issues, automated medical diagnosis, analyzing information in surgical videos, ensuring timely communication and transportation during health disasters and emergencies, for optimizing expenditures, and more.
R 9,157.00
Artificial Intelligence, Engineering Systems and Sustainable Development
Development in any country is impossible if reliable and affordable energy, safe water and sanitation, as well as telecommunication facilities, are not easily accessible. Artificial intelligence and machine learning techniques are now widely used in all branches of engineering to build and optimize systems. The combination of AI and engineering can indeed act as a real catalyst to achieve the UN SDGs.The volume editors present an analysis of different concepts and case studies in engineering disciplines such as chemical, civil, electrical, telecommunications and mechanical engineering, demonstrating how engineering systems and processes can leverage the power of AI to drive and achieve the UN SDGs. Topics covered include sustainable crop production and consumption, AI based clean water and sanitation monitoring, intelligent transport systems and achieving affordable and clean energy through AI and 5G powered internet of energy.Such a study is of paramount importance and is a valuable source of information for researchers, engineers, and policy makers to be able to better design and adopt AI enabled techniques in different engineering areas, with a view to catalyze the achievement of the UN SDGs.
R 4,520.03
Artificial Intelligence and Smart Vehicles
This book constitutes the refereed proceedings of the First International Conference on Artificial Intelligence and Smart Vehicles, ICAISV 2023, held in Tehran, Iran, during January 25–26, 2023.The 14 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections as follows: machine learning, data mining, machine vision, image processing, signal analysis, decision support systems, expert systems, and their applications in smart vehicles.
R 3,307.38
Artificial Intelligence and Scientific Method
This work examines the advances made in the field of AI over the past 20 years, discussing their profound implications for philosophy. Taking a non-technical approach, Donald Gillies focuses on two key topics within AI: machine learning in the Turing tradition and the development of logic programming and its connection with non-monotonic logic. Demonstrating how current views on scientific method are challenged by this recent research, he goes on to suggest a new framework for the study of logic. Finally, Professor Gillies draws on work by such seminal thinkers as Bacon, G'odel, Popper, Penrose, and Lucas to address the hotly contested question of whether computers might become intellectually superior to human beings.
R 6,961.00
Artificial Intelligence in Chemistry and Chemical Engineering
Integrate AI into chemical research through structured tutorials and exercises Chemists adopting AI methods need discipline-specific training beyond generic introductions. Artificial Intelligence in Chemistry and Chemical Engineering: From Basics to Practical Exercises provides a step-by-step tutorial guiding researchers through AI, automation, data science, and cheminformatics. Progressing from foundational concepts to advanced applications, hands-on exercises and real-world case studies enable direct application to ongoing research programs. Coverage spans AI reaction prediction models, automated high-throughput synthesis platforms, and chemical reaction big data systems. The book addresses ethical implications and regulatory considerations for AI deployment in chemistry. A companion website and a specialized large language model deliver continuous interactive support, providing updated resources and ongoing learning opportunities beyond the printed text. Readers will also find: Foundational machine learning concepts tailored specifically for practitioners working in chemistry and chemical engineering research disciplinesDetailed tutorials on building and utilizing chemical reaction big data systems for accelerating discovery and optimizing workflowsReal-world case studies demonstrating how AI-driven approaches solve specific challenges in organic synthesis and molecular scienceDiscussion of potential misuse scenarios and regulatory frameworks to navigate responsible AI integration in laboratory settingsPractical guidance on constructing next-generation automated high-throughput synthesis platforms for efficient experimental design and execution Designed for organic, physical, theoretical, medicinal, analytical, pharmaceutical, and environmental chemists, as well as materials scientists, chemical engineers, and computer scientists, this book delivers the structured training required to apply AI methods directly to chemical research and industrial practice.
R 4,299.00
Intuitive Exploration of Artificial Intelligence
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future.An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential.The book is intended to serve as a textbook for graduate and senior-level undergraduate courses in AI. Moreover, since the book provides a strong geometrical intuition about advanced mathematical foundations of AI, practitioners and researchers will equally benefit from the book.
R 2,381.00
Artificial Intelligence for Neuroscience and Emotional Systems
The two volume set LNCS 14674 and 14675 constitutes the proceedings of the 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, which took place in Olhâo, Portugal, during June 4–7, 2024.The 99 full papers presented in these proceedings were carefully reviewed and selected from 193 submissions. They were organized in topical sections as follows:Part I: Machine learning in neuroscience; artificial intelligence in neurophysiology; neuromotor and cognitive disorders; intelligent systems for assessment, treatment, and assistance in early stages of Alzheimer's disease and other dementias; socio-cognitive, affective and physiological computing; affective computing and context awareness in ambientintelliigence; learning tools to lecture;Part II: Machine learning in computer vision and robotics; bio-inspired computing approaches; social and civil engineering through human AI translations; smart renewable energies: advancing AI algorithms in the renewable energy industry; bioinspired applications.
R 3,553.87
Artificial Intelligence in Biomedical and Modern Healthcare Informatics
Artificial Intelligence in Biomedical and Modern Healthcare Informatics provides a deeper understanding of current trends in AI and machine learning within health care diagnosis. Its practical approach in healthcare gives insights into wearable sensors and device modules to help doctors and their patients in enhanced healthcare systems. The book helps readers detect common difficulties and their solutions for early detection and prediction of any disease. In 34 chapters, the book provides beginners and experts in the medical science field with general pictures and detailed descriptions of imaging and signal processing principles and clinical applications. With forefront applications and up-to-date analytical methods, this book captures the interests of colleagues in the medical imaging research field and is a valuable resource for healthcare professionals who wish to understand the principles and applications of signal and image processing and its related technologies in healthcare.
R 4,414.00
Tracking and Preventing Diseases with Artificial Intelligence
This book presents an overview of how machine learning and data mining techniques are used for tracking and preventing diseases. It covers several aspects such as stress level identification of a person from his/her speech, automatic diagnosis of disease from X-ray images, intelligent diagnosis of Glaucoma from clinical eye examination data, prediction of protein-coding genes from big genome data, disease detection through microscopic analysis of blood cells, information retrieval from electronic medical record using named entity recognition approaches, and prediction of drug-target interactions.The book is suitable for computer scientists having a bachelor degree in computer science. The book is an ideal resource as a reference book for teaching a graduate course on AI for Medicine or AI for Health care. Researchers working in the multidisciplinary areas use this book to discover the current developments. Besides its use in academia, this book provides enough details about the state-of-the-art algorithms addressing various biomedical domains, so that it could be used by industry practitioners who want to implement AI techniques to analyze the diseases. Medical institutions use this book as reference material and give tutorials to medical experts on how the advanced AI and ML techniques contribute to the diagnosis and prediction of the diseases.
R 7,450.27
Artificial Intelligence And Beyond For Finance
Why did we write this book? We wanted to help financial experts and investors to understand the state-of-the-art of artificial intelligence and machine learning in finance. And so, what is artificial intelligence?The foundations of artificial intelligence lie in the human desire to automate. Often this desire has had foundations in grand civilization-making visions or economic needs, such as the Antikythera mechanism, circa 200 BCE. Considered to be the oldest known example of an analog computer, it is believed that the mechanism automated the prediction of the positions of the sun, the moon, and the planets used to assist in navigation.No matter the specific industry or application, AI has become a new engine of growth. Both finance and banking have been leveraging AI technologies and algorithms, applying them to automate routine tasks, procedures, forecasting, thereby improving overall customer experience.The topics covered in this book make it an invaluable resource for academics, researchers, policy makers, and practitioners alike who want to understand how AI has affected the banking and financial industries and how it will continue to change them in the years to come.
R 6,322.49
Artificial Intelligence and Conservation
With the increasing public interest in artificial intelligence (AI), there is also increasing interest in learning about the benefits that AI can deliver to society. This book focuses on research advances in AI that benefit the conservation of wildlife, forests, coral reefs, rivers, and other natural resources. It presents how the joint efforts of researchers in computer science, ecology, economics, and psychology help address the goals of the United Nations' 2030 Agenda for Sustainable Development. Written at a level accessible to conservation professionals and AI researchers, the book offers both an overview of the field and an in-depth view of how AI is being used to understand patterns in wildlife poaching and enhance patrol efforts in response, covering research advances, field tests and real-world deployments. The book also features efforts in other major conservation directions, including protecting natural resources, ecosystem monitoring, and bio-invasion management through the use of game theory, machine learning, and optimization.
R 2,365.61
Artificial Intelligence
This two-volume set LNAI 14473-14474 constitutes revised selected papers presented at the Third CAAI International Conference, CICAI 2023, in Fuzhou, China, in July 2023. CICAI is a summit forum in the field of artificial intelligence and the 2023 forum was hosted by Chinese Association for Artificial Intelligence (CAAI). The 100 papers were thoroughly reviewed and selected from 376 submissions. CICAI 2023 conference covers a wide range of of AI generated content, computer vision, machine learning, nature language processing, application of AI, and data mining, amongst others.
R 3,940.98
Learning for the Age of Artificial Intelligence
Learning for the Age of Artificial Intelligence is a richly informed argument for curricular change to educate people towards achievement and success as intelligent machine systems proliferate. Describing eight key competences, this comprehensive volume prepares educational leaders, designers, researchers, and policymakers to effectively rethink the knowledge, skills, and environments that students need to thrive and avoid displacement in today’s technology-enhanced culture and workforce. Essential insights into school operations, machine learning, complex training and assessment, and economic challenges round out this cogent, relatable discussion about the imminent evolution of the education sector.
R 2,542.90
Artificial Intelligence for Future Networks
An exploration of connected intelligent edge, artificial intelligence, and machine learning for B5G/6G architecture Artificial Intelligence for Future Networks illuminates how artificial intelligence (AI) and machine learning (ML) influence the general architecture and improve the usability of future networks like B5G and 6G through increased system capacity, low latency, high reliability, greater spectrum efficiency, and support of massive internet of things (mIoT). The book reviews network design and management, offering an in-depth treatment of AI oriented future networks infrastructure. Providing up-to-date materials for AI empowered resource management and extensive discussion on energy-efficient communications, this book incorporates a thorough analysis of the recent advancement and potential applications of ML and AI in future networks. Each chapter is written by an expert at the forefront of AI and ML research, highlighting current design and engineering practices and emphasizing challenging issues related to future wireless applications. Some of the topics include: Signal processing and detection, covering preprocess and level signals, transform signals and extract features, and training and deploying AI models and systemsChannel estimation and prediction, covering channel characteristics, modeling, and classic learning-aided and AI-aided estimation techniquesResource allocation, covering resource allocation optimization and efficient power consumption for different computing paradigms such as Cloud, Edge, Fog, IoT, and MECAntenna design using AI, covering basics of antennas, EM simulator/optimization algorithms, and surrogate modeling Identifying technical roadblocks and sharing cutting-edge research on developing methodologies, Artificial Intelligence for Future Networks is an essential reference on the subject for professionals and researchers involved in the field of wireless communications and networks, along with graduate and PhD students in electrical and computer engineering programs of study.
R 4,559.00
Artificial Intelligence and Accounting
In the dynamic field of accounting, where accuracy and productivity are critical, artificial intelligence (AI) integration has become a game-changer and AI is set to affect every industry. With the speed at which technology is developing, a thorough manual that helps readers understand the complex world of AI in accounting is desperately needed. By offering a sophisticated grasp of how AI is changing the core ideas of accounting and financial management, this book bridges this knowledge gap. It explores the relationship between AI technology and accounting processes, revealing the significant influence and unrealised potential outside of traditional bookkeeping.This book delves into how AI is revolutionising accounting procedures. It explores the newest AI technologies and their uses in financial data processing, auditing, compliance, and forecasting, ranging from machine learning to predictive analytics. It ensures responsible AI integration by addressing biases, accountability, and transparency while emphasising ethical considerations. This book provides case studies, practical advice, and examples from the real world, guaranteeing that readers not only understand the theoretical foundations of AI in accounting but also get the knowledge necessary to apply and maximise these technologies within their professional domains by connecting theory and application. It offers a road map for traversing the accounting industry's AI frontier, from using predictive analytics to make well-informed decisions to automating repetitive activities.This book will enable accountants, auditors, and financial analysts to prosper in the emerging AI-driven world.
R 9,315.40
Understanding Artificial Intelligence
Understanding Artificial Intelligence Provides students across majors with a clear and accessible overview of new artificial intelligence technologies and applications Artificial intelligence (AI) is broadly defined as computers programmed to simulate the cognitive functions of the human mind. In combination with the Neural Network (NN), Big Data (BD), and the Internet of Things (IoT), artificial intelligence has transformed everyday life: self-driving cars, delivery drones, digital assistants, facial recognition devices, autonomous vacuum cleaners, and mobile navigation apps all rely on AI to perform tasks. With the rise of artificial intelligence, the job market of the near future will be radically different???many jobs will disappear, yet new jobs and opportunities will emerge. Understanding Artificial Intelligence: Fundamentals and Applications covers the fundamental concepts and key technologies of AI while exploring its impact on the future of work. Requiring no previous background in artificial intelligence, this easy-to-understand textbook addresses AI challenges in healthcare, finance, retail, manufacturing, agriculture, government, and smart city development. Each chapter includes simple computer laboratories to teach students how to develop artificial intelligence applications and integrate software and hardware for robotic development. In addition, this text: Focuses on artificial intelligence applications in different industries and sectorsTraces the history of neural networks and explains popular neural network architecturesCovers AI technologies, such as Machine Vision (MV), Natural Language Processing (NLP), and Unmanned Aerial Vehicles (UAV)Describes various artificial intelligence computational platforms, including Google Tensor Processing Unit (TPU) and Kneron Neural Processing Unit (NPU)Highlights the development of new artificial intelligence hardware and architectures Understanding Artificial Intelligence: Fundamentals and Applications is an excellent textbook for undergraduates in business, humanities, the arts, science, healthcare, engineering, and many other disciplines. It is also an invaluable guide for working professionals wanting to learn about the ways AI is changing their particular field.
R 3,745.00
R 809.45
Machine Learning in Medicine
Machine Learning in Medicine covers the state-of-the-art techniques of machine learning and their applications in the medical field. It presents several computer-aided diagnosis (CAD) systems, which have played an important role in the diagnosis of several diseases in the past decade, e.g., cancer detection, resulting in the development of several successful systems.New developments in machine learning may make it possible in the near future to develop machines that are capable of completely performing tasks that currently cannot be completed without human aid, especially in the medical field. This book covers such machines, including convolutional neural networks (CNNs) with different activation functions for small- to medium-size biomedical datasets, detection of abnormal activities stemming from cognitive decline, thermal dose modelling for thermal ablative cancer treatments, dermatological machine learning clinical decision support systems, artificial intelligence-powered ultrasound for diagnosis, practical challenges with possible solutions for machine learning in medical imaging, epilepsy diagnosis from structural MRI, Alzheimer's disease diagnosis, classification of left ventricular hypertrophy, and intelligent medical language understanding.This book will help to advance scientific research within the broad field of machine learning in the medical field. It focuses on major trends and challenges in this area and presents work aimed at identifying new techniques and their use in biomedical analysis, including extensive references at the end of each chapter.
R 4,462.69
Artificial Intelligence Programming with Python
A hands-on roadmap to using Python for artificial intelligence programming In Practical Artificial Intelligence Programming with Python: From Zero to Hero, veteran educator and photophysicist Dr. Perry Xiao delivers a thorough introduction to one of the most exciting areas of computer science in modern history. The book demystifies artificial intelligence and teaches readers its fundamentals from scratch in simple and plain language and with illustrative code examples. Divided into three parts, the author explains artificial intelligence generally, machine learning, and deep learning. It tackles a wide variety of useful topics, from classification and regression in machine learning to generative adversarial networks. He also includes: Fulsome introductions to MATLAB, Python, AI, machine learning, and deep learningExpansive discussions on supervised and unsupervised machine learning, as well as semi-supervised learningPractical AI and Python “cheat sheet” quick referencesThis hands-on AI programming guide is perfect for anyone with a basic knowledge of programming—including familiarity with variables, arrays, loops, if-else statements, and file input and output—who seeks to understand foundational concepts in AI and AI development.
R 958.00
Artificial Intelligence for Marketing
A straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the "need-to-know" aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way. Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. Straightforward, pragmatic, and with no math required, this book will help you: Speak intelligently about Artificial Intelligence and its advantages in marketingUnderstand how marketers without a Data Science degree can make use of machine learning technologyCollaborate with data scientists as a subject matter expert to help develop focused-use applicationsHelp your company gain a competitive advantage by leveraging leading-edge technology in marketing Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve.
R 1,186.00
Machine Learning For Dummies
The most human-friendly book on machine learning Somewhere buried in all the systems that drive artificial intelligence, you'll find machine learning—the process that allows technology to build knowledge based on data and patterns. Machine Learning For Dummies is an excellent starting point for anyone who wants deeper insight into how all this learning actually happens. This book offers an overview of machine learning and its most important practical applications. Then, you'll dive into the tools, code, and math that make machine learning go—and you'll even get step-by-step instructions for testing it out on your own. For an easy-to-follow introduction to building smart algorithms, this Dummies guide is your go-to. Piece together what machine learning is, what it can do, and what it can't doLearn the basics of machine learning code and how it integrates with large datasetsUnderstand the mathematical principles that AI uses to make itself smarterConsider real-world applications of machine learning and write your own algorithms With clear explanations and hands-on instruction, Machine Learning For Dummies is a great entry-level resource for developers looking to get started with AI and machine learning.
R 798.00
Artificial Intelligence in Bioinformatics and Chemoinformatics
The authors aim to shed light on the practicality of using machine learning in finding complex chemoinformatics and bioinformatics applications as well as identifiying AI in biological and chemical data points. The chapters are designed in such a way that they highlight the important role of AI in chemistry and bioinformatics particularly for the classification of diseases, selection of features and compounds, dimensionality reduction and more. In addition, they assist in the organization and optimal use of data points generated from experiments performed using AI techniques. This volume discusses the development of automated tools and techniques to aid in research plans. Features Covers AI applications in bioinformatics and chemoinformatics. Demystifies the involvement of AI in generating biological and chemical data. Provides an Introduction to basic and advanced chemoinformatics computational tools. Presents a chemical biology based toolset for artificial intelligence usage in drug design. Discusses computational methods in cancer, genome mapping and stem cell research.
R 9,349.08
Artifictional Intelligence
Recent startling successes in machine intelligence using a technique called ‘deep learning’ seem to blur the line between human and machine as never before. Are computers on the cusp of becoming so intelligent that they will render humans obsolete? Harry Collins argues we are getting ahead of ourselves, caught up in images of a fantastical future dreamt up in fictional portrayals. The greater present danger is that we lose sight of the very real limitations of artificial intelligence and readily enslave ourselves to stupid computers: the ‘Surrender’. By dissecting the intricacies of language use and meaning, Collins shows how far we have to go before we cannot distinguish between the social understanding of humans and computers. When the stakes are so high, we need to set the bar higher: to rethink ‘intelligence’ and recognize its inherent social basis. Only if machine learning succeeds on this count can we congratulate ourselves on having produced artificial intelligence.
R 2,563.00
Artificial Intelligence and Conservation
With the increasing public interest in artificial intelligence (AI), there is also increasing interest in learning about the benefits that AI can deliver to society. This book focuses on research advances in AI that benefit the conservation of wildlife, forests, coral reefs, rivers, and other natural resources. It presents how the joint efforts of researchers in computer science, ecology, economics, and psychology help address the goals of the United Nations' 2030 Agenda for Sustainable Development. Written at a level accessible to conservation professionals and AI researchers, the book offers both an overview of the field and an in-depth view of how AI is being used to understand patterns in wildlife poaching and enhance patrol efforts in response, covering research advances, field tests and real-world deployments. The book also features efforts in other major conservation directions, including protecting natural resources, ecosystem monitoring, and bio-invasion management through the use of game theory, machine learning, and optimization.
R 5,979.79
R 579.00
Artificial Intelligence in Decision Sciences
Artificial Intelligence in Decision Science investigates the impact of artificial intelligence (AI) on decision-making. The book is a well-balanced mix of theory, practice and examples from the field to show how AI-based techniques can help in making data-driven decisions across a range of sectors, including business, healthcare, finance, manufacturing, education and public administration. This book explores the fundamental concepts of AI, such as machine learning, deep learning, natural language processing, generative AI and multi-agent systems, and their role in addressing modern decision-making problems. Practical insights are given on the adoption of AI, on how to implement AI and the impact of AI in case-study organization, which makes concepts accessible for researchers and practitioners alike. This book is an excellent reference guide for academics, students, industry and decision makers interested in effective application of AI techniques in the current context of decision sciences to facilitate smart, effective and informative decision making.
R 5,536.00
Dialogues on Minds, Machines, and AI
Dialogues on Minds, Machines, and AI invites readers into a series of thought-provoking debates among three college seniors bound for graduate school: Sue, completing her double major in philosophy and cognitive science; John, a computer engineering specialist; and Amy, a psychology major. Through five engaging lunchtime conversations, these students bring their diverse perspectives to fundamental questions about consciousness, artificial intelligence, and the nature of mind.The dialogues seamlessly blend discussions of popular science fiction films with critical examinations of recent AI developments, including ChatGPT, deep fakes, and other emerging technologies. Readers will explore foundational concepts at the intersection of human consciousness and machine learning: Alan Turing's influential "imitation game," John Searle's provocative "Chinese room argument," computational theories of mind, robot creativity, and the modularity of mind hypothesis. Rather than advocating for any particular viewpoint, these conversations illuminate the strengths, weaknesses, and implications of each perspective.Perfect for undergraduate students and curious minds from all backgrounds, this accessible introduction to cognitive science requires no prior knowledge of philosophy or technical subjects. The book includes a comprehensive glossary and thoughtful study questions to enhance understanding, while a carefully curated bibliography enables readers to explore specific topics in greater depth.
R 9,303.07
