Search results for: applications-of-artificial-intelligence-and-machine-learning

Applications of Artificial Intelligence and Machine Learning

Author : Bhuvan Unhelker
File Size : 25.48 MB
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The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning—ICAAAIML 2021. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in health care, agriculture, business, and security. This book contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book is a valuable resource for students, academics, and practitioners in the industry working on AI applications.

Applications of Artificial Intelligence and Machine Learning

Author : Ankur Choudhary
File Size : 35.97 MB
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The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business, and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics, and practitioners in the industry working on AI applications.

Applications of Artificial Intelligence AI and Machine Learning ML in the Petroleum Industry

Author : Manan Shah
File Size : 86.42 MB
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Today, raw data on any industry is widely available. With the help of artificial intelligence (AI) and machine learning (ML), this data can be used to gain meaningful insights. In addition, as data is the new raw material for today’s world, AI and ML will be applied in every industrial sector. Industry 4.0 mainly focuses on the automation of things. From that perspective, the oil and gas industry is one of the largest industries in terms of economy and energy. Applications of Artificial Intelligence (AI) and Machine Learning (ML) in the Petroleum Industry analyzes the use of AI and ML in the oil and gas industry across all three sectors, namely upstream, midstream, and downstream. It covers every aspect of the petroleum industry as related to the application of AI and ML, ranging from exploration, data management, extraction, processing, real-time data analysis, monitoring, cloud-based connectivity system, and conditions analysis, to the final delivery of the product to the end customer, while taking into account the incorporation of the safety measures for a better operation and the efficient and effective execution of operations. This book explores the variety of applications that can be integrated to support the existing petroleum and adjacent sectors to solve industry problems. It will serve as a useful guide for professionals working in the petroleum industry, industrial engineers, AI and ML experts and researchers, as well as students.

Artificial Intelligence Machine Learning and Data Science Technologies

Author : Neeraj Mohan
File Size : 24.15 MB
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This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.

Tools and Applications with Artificial Intelligence

Author : Constantinos Koutsojannis
File Size : 53.83 MB
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In recent years, the use of Artificial Intelligence (AI) techniques has been greatly increased. The term “intelligence” seems to be a “must” in a large number of European and International project calls. AI Techniques have been used in almost any domain. Application-oriented systems usually incorporate some kind of “intelligence” by using techniques stemming from intelligent search, knowledge representation, machine learning, knowledge discovery, intelligent agents, computational intelligence etc. The Workshop on “Applications with Artificial Intelligence” seeks for quality papers on computer applications that incorporate some kind of AI technique. The objective of the workshop was to bring together scientists, engineers and practitioners, who work on designing or developing applications that use intelligent techniques or work on intelligent techniques and apply them to application domains (like medicine, biology, education etc), to present and discuss their research works and exchange ideas in this book.

Risk Modeling

Author : Terisa Roberts
File Size : 31.66 MB
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A wide-ranging overview of the use of machine learning and AI techniques in financial risk management, including practical advice for implementation Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning introduces readers to the use of innovative AI technologies for forecasting and evaluating financial risks. Providing up-to-date coverage of the practical application of current modelling techniques in risk management, this real-world guide also explores new opportunities and challenges associated with implementing machine learning and artificial intelligence (AI) into the risk management process. Authors Terisa Roberts and Stephen Tonna provide readers with a clear understanding about the strengths and weaknesses of machine learning and AI while explaining how they can be applied to both everyday risk management problems and to evaluate the financial impact of extreme events such as global pandemics and changes in climate. Throughout the text, the authors clarify misconceptions about the use of machine learning and AI techniques using clear explanations while offering step-by-step advice for implementing the technologies into an organization’s risk management model governance framework. This authoritative volume: Highlights the use of machine learning and AI in identifying procedures for avoiding or minimizing financial risk Discusses practical tools for assessing bias and interpretability of resultant models developed with machine learning algorithms and techniques Covers the basic principles and nuances of feature engineering and common machine learning algorithms Illustrates how risk modeling is incorporating machine learning and AI techniques to rapidly consume complex data and address current gaps in the end-to-end modelling lifecycle Explains how proprietary software and open-source languages can be combined to deliver the best of both worlds: for risk models and risk practitioners Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning is an invaluable guide for CEOs, CROs, CFOs, risk managers, business managers, and other professionals working in risk management.

Machine Learning and Artificial Intelligence with Industrial Applications

Author : Diego Carou
File Size : 36.46 MB
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Artificial Intelligence and Machine Learning in Healthcare

Author : Ankur Saxena
File Size : 39.85 MB
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This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.

Artificial Intelligence

Author : Victor Servings
File Size : 59.28 MB
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Some things you will come across, as Ai sweeps all over the world and helps and threatens everyone at the same time: The very definition of artificial intelligence. Business opportunities that increase with the help of Ai. How machine learning ties into all of this. What neural networks are. Robotics and their role in society. The pros and cons of artificial intelligence. Which kinds of Ai have already contributed to the way we accelerate our systems. The main concepts of Ai and what they mean. How they contribute to the job market. What artificial intelligence can do in our daily lives. There is so much more to it! Feed your curiosity and indulge yourself in the elaborate knowledge in this brief guide!

Applications of Artificial Intelligence and Machine Learning in Healthcare

Author : Hassan Alamoudi
File Size : 76.52 MB
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Artificial Intelligence (AI) is becoming a ubiquitous term that is used in many fields of research or the popular culture. Among these fields that was affected by this hype is the healthcare sector. Along with its subdomain, Machine Learning (ML), they established an environment of interest in the promises of machines versus humans capabilities. Though artificial intelligence applications in healthcare such as interpreting ECGs could date back to the mid of the twentieth century, the promises of AI still at its beginning when it comes to new breakthroughs. This is due to the transformation into a digital world and new advancements in the processing capabilities. Computer vision has contributed the most to the healthcare sector where it can leverage doctors and practitioners with automated classification and annotations as a preparing step. This kind of mechanism is the best suited for applications of AI in healthcare. However, the amount of data in other forms such as textual or lab results is exceeding the force power. While a solution could be to use machines to learn and propose solutions, the results could be catastrophic and human lives are on stake. So, explainable AI could be beneficial where it analyzes and makes predictions that can be trusted by the users. The study here is conducted on cardiovascular patients dataset to predict the presence or absence of the disease. Classifications techniques used include Nave Bayes, Logistic Regression, Decision Trees, Support Vector Machines, and Artificial Neural Networks. The Logistic regression model achieved the best Area under the curve. Moreover, an extension of the previous studies discussed is conducted to explain the model and to show how models of AI can be trusted and not used as black-boxes.