Artificial intelligence is a word that carries with it heavy connotations. Although artificial intelligence is nothing more than the capacity for logic and understanding that machines can exhibit, in the minds of most people artificial intelligence is almost a Pandora's box that, when opened, will eventually signal the human race's doom..
The idea that machines pose an existential threat to human beings has been around for at least 60 years. It goes something like this: intelligent machines eventually realize the uselessness of human beings and turn against their creators. Or this: intelligent machines reduce human to cattle or even food after a dramatic war that human beings lose.
Human beings have created countless languages and writing systems that have allowed us to expand collective human knowledge over a period of thousands of years. Much of the knowledge that we utilized today, knowledge about the math, science, and the stars, originates from observations made thousands of years ago but which were recorded by writing systems, allowing this knowledge to be preserved and passed down.
Artificial intelligence has been used for many business, financial, medical, and other applications, and scientists and researchers are actively studying how these applications can be expanded to make human life simpler.
The applications of AI will be explored in this book, both the real applications to business, finance, medicine, and health and the theoretical applications. Even the sensational, perhaps exaggerated applications of AI will be explored in the context of taking a look at how AI may potentially be applied in the future. The purpose of this discussion is for the reader to understand what AI is by understanding how it is used.
Artificial intelligence is certainly a blessing at this point, but the reality that it may become a curse is not lost on some people. Understanding the full implications of AI requires a deep knowledge of what it is and where it came from.
For companies and businesses to take advantage of AI-powered and improved interactions, the conversation has to begin inside the organization. Leaders are supposed to start with the available channels and improve their smartness. From that point, they are supposed to ask key questions about engagements with customers and employees.
Here is a preview of what you will learn...
Brief history of artificial intelligence
The state of art of machine learning
Artificial neural networks applied to machine learning
How can we build an AI ready culture
Our daily lives with AI
And More.....
Автор: Saman K. Halgamuge; Lipo Wang Название: Computational Intelligence for Modelling and Prediction ISBN: 3642065414 ISBN-13(EAN): 9783642065415 Издательство: Springer Рейтинг: Цена: 26711.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The range of the various applications is captured with 5 chapters in image processing, 2 chapters in audio processing, 3 chapters in commerce and finance, 2 chapters in communication networks and 6 chapters containing other applications.
Автор: Babita Pandey, Aditya Khamparia Название: Hidden Link Prediction in Stochastic Social Networks ISBN: 152259096X ISBN-13(EAN): 9781522590965 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28552.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Link prediction is required to understand the evolutionary theory of computing for different social networks. However, the stochastic growth of the social network leads to various challenges in identifying hidden links, such as representation of graph, distinction between spurious and missing links, selection of link prediction techniques comprised of network features, and identification of network types. Hidden Link Prediction in Stochastic Social Networks concentrates on the foremost techniques of hidden link predictions in stochastic social networks including methods and approaches that involve similarity index techniques, matrix factorization, reinforcement, models, and graph representations and community detections. The book also includes miscellaneous methods of different modalities in deep learning, agent-driven AI techniques, and automata-driven systems and will improve the understanding and development of automated machine learning systems for supervised, unsupervised, and recommendation-driven learning systems. It is intended for use by data scientists, technology developers, professionals, students, and researchers.
Автор: Jalal Kawash; Nitin Agarwal; Tansel ?zyer Название: Prediction and Inference from Social Networks and Social Media ISBN: 3319510487 ISBN-13(EAN): 9783319510484 Издательство: Springer Рейтинг: Цена: 14635.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the challenges of social network and social media analysis in terms of prediction and inference. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection.
Автор: Duc T. Pham; Xing Liu Название: Neural Networks for Identification, Prediction and Control ISBN: 1447132467 ISBN-13(EAN): 9781447132462 Издательство: Springer Рейтинг: Цена: 6097.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. The neural network types considered in detail are the muhilayer perceptron (MLP), the Elman and Jordan networks and the Group-Method-of-Data-Handling (GMDH) network.
Автор: Cherry Bhargava Название: AI Techniques for Reliability Prediction for Electronic Components ISBN: 1799814645 ISBN-13(EAN): 9781799814641 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 30215.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry.
AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.
Описание: In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.
Автор: Kawash Jalal, Agarwal Nitin, Цzyer Tansel Название: Prediction and Inference from Social Networks and Social Media ISBN: 3319845535 ISBN-13(EAN): 9783319845531 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the challenges of social network and social media analysis in terms of prediction and inference. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection.
Автор: Zhou Wuneng, Yang Jun, Zhou Liuwei Название: Stability and Synchronization Control of Stochastic Neural Networks ISBN: 3662517167 ISBN-13(EAN): 9783662517161 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control.
Описание: This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL methods to training your agent to beat arcade ...
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