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: Yogendra Narayan Pandey et al Название: Machine learning in the oil and gas industry ISBN: 1484260937 ISBN-13(EAN): 9781484260937 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches.
The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering.
Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will LearnUnderstanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industryGet the basic concepts of computer programming and machine and deep learning required for implementing the algorithms usedStudy interesting industry problems that are good candidates for being solved by machine and deep learningDiscover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.
Автор: Patrick Bangert Название: Machine learning and data science in the oil and gas industry ISBN: 0128207140 ISBN-13(EAN): 9780128207147 Издательство: Elsevier Science Рейтинг: Цена: 125760.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value.
Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful
Gain practical understanding of machine learning used in oil and gas operations through contributed case studies
Learn change management skills that will help gain confidence in pursuing the technology
Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)
Автор: Edited By G. Rajesh, X. Mercilin Raajini, Hien Dan Название: Industry 4.0 interoperability, analytics, security, and case studies / ISBN: 0367501120 ISBN-13(EAN): 9780367501129 Издательство: Taylor&Francis Рейтинг: Цена: 168430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: All over the world, vast research is in progress on the domain of industry 4.0 and related techniques. Industry 4.0 is expected to have a very high impact on labor markets, global value chains, education, health, environment, and many social economic aspects.
Автор: Abdul Karim Название: Theoretical, Modelling and Numerical Simulations Toward Industry 4.0 ISBN: 9811589860 ISBN-13(EAN): 9789811589867 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents theoretical modeling and numerical simulations applied to drive several applications towards Industrial Revolution 4.0 (IR 4.0). The topics discussed range from theoretical parts to extensive simulations involving many efficient algorithms as well as various statistical techniques.
Автор: Raut Roshani, Mihovska Albena Dimitrova Название: Examining the Impact of Deep Learning and IoT on Multi-Industry Applications, 1 volume ISBN: 1799883582 ISBN-13(EAN): 9781799883586 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 196810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings.
Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers' points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.
Автор: Max Hoffmann Название: Smart Agents for the Industry 4.0 ISBN: 3658277440 ISBN-13(EAN): 9783658277444 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Max Hoffmann describes the realization of a framework that enables autonomous decision-making in industrial manufacturing processes by means of multi-agent systems and the OPC UA meta-modeling standard.
Автор: Jos? R?os; Alain Bernard; Abdelaziz Bouras; Sebti Название: Product Lifecycle Management and the Industry of the Future ISBN: 3319892215 ISBN-13(EAN): 9783319892214 Издательство: Springer Рейтинг: Цена: 137890.00 T Наличие на складе: Поставка под заказ. Описание: This book constitutes the refereed post-conference proceedings of the 14th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2017, held in Seville, Spain, in July 2017. The 64 revised full papers presented were carefully reviewed and selected from 78 submissions.
Автор: Maria Mach-Kr?l; Celina M. Olszak; Tomasz Pe?ech-P Название: Advances in ICT for Business, Industry and Public Sector ISBN: 3319113275 ISBN-13(EAN): 9783319113272 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A Multi-level Hierarchical Approach for Configuring Business Processes.- Profiling simulation performance: The example of the German toll system.- Analysis of Content of Posts and Comments in Evolving Social Groups.- Generation of Hierarchical Business Process Models from Attribute Relationship Diagrams.- Nonlinear Time Structures and Nonlinear Time Ontology for Description of Economic Phenomena.- Business Intelligence and Analytics in Organizations.- Low-frequency Signal Reconstruction and Abrupt Change Detection in Non-Stationary Time Series by Enhanced Moving Trend Based Filters.- The Assessment of the EPQ Parameter for Detecting H-Index Manipulation and the Analysis of Scientific Publications.- Fuzzy Multi-attribute Evaluation of Investments.- Theory of digital data processing in the ICT.- The opportunities and challenges connected with implementation of the Big Data concept.
Автор: Bangert, Patrick Название: Machine Learning And Data Science In The Power Generation Industry ISBN: 0128197420 ISBN-13(EAN): 9780128197424 Издательство: Elsevier Science Рейтинг: Цена: 121270.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Machine Learning and Data Science in the Power Generation Industry: Best Practices, Tools, and Case Studies explores current best practices and quantifies the value-add in developing data-oriented computational programs in the energy industry, with a focus on real-world case studies selected from modern practice. The book provides a set of realistic pathways for organizations seeking to develop machine learning methods, with discussion on data selection and curation, as well as organizational implementation in terms of staffing and continuing operationalization. The book articulates a body of case study-driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, emissions credits, and forecasting.
Название: Era of artificial intelligence, machine learning, and data science in the pharmaceutical industry ISBN: 0128200456 ISBN-13(EAN): 9780128200452 Издательство: Elsevier Science Рейтинг: Цена: 110030.00 T Наличие на складе: Поставка под заказ. Описание: Collins Explore English is a 6-level course which provides full coverage of the Cambridge Primary English as a Second Language curriculum framework (0057) from 2020. With a magazine-style Student`s Resource Book, comprehensive Student`s Coursebook, and supportive Teacher`s Guide, it offers clear progression within and across levels.
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