If you are curious about the basics of artificial intelligence, blockchain technology, and quantum computing as key enablers for digital transformation and innovation, Digital Fluency is your handy guide. The real-world applications of these cutting-edge technologies are expanding rapidly, and your daily life will continue to be affected by each of them. There is no better time than now to get started and become digitally fluent.
You need not have previous knowledge of these versatile technologies, as author Volker Lang will expertly guide you through this digital age. He illustrates key concepts and applications in numerous practical examples and more than 48 catchy figures throughout Digital Fluency. The end of each chapter presents you with a helpful implementation checklist of central lessons before proceeding to the next. This book gets to the heart of digital buzzwords and concepts, and tells you what they truly mean.
Breaking down topics such as automated driving and intelligent robotics powered by artificial intelligence, blockchain-based cryptocurrencies and smart contracts, drug development and optimization of financial investment portfolios by quantum computing, and more is imperative to being ready for what the future of industry holds. Whether your own digital transformation journey takes place within your private or public organization, your studies, or your individual household, Digital Fluency maps out a concrete digital action plan for all of your technology and innovation strategy needs.
What You Will Learn
Gain guidance in the digital age without requiring any previous knowledge about digital technologies and digital transformation
Get acquainted with the most popular current and prospective applications of artificial intelligence, blockchain technology, and quantum computing across a wide range of industries including healthcare, financial services, and the automobile industry
Become familiar with the digital innovation models of Amazon, Google, Microsoft, IBM, and other world-leading organizations
Implement your own digital transformation successfully along the eight core dimensions of a concrete digital action plan
Who This Book Is For
Thought-leaders, business executives and industry strategists, management and strategy consultants, politicians and policy makers, entrepreneurs, financial analysts, investors and venture capitalists, students and research scientists, as well as general readers, who want to become digitally fluent.
Автор: Copeland, B. Jack. Название: The Essential Turing ISBN: 0198250800 ISBN-13(EAN): 9780198250807 Издательство: Oxford Academ Рейтинг: Цена: 33250.00 T Наличие на складе: Есть Описание: The ideas that gave birth to the computer age Alan Turing, pioneer of computing and World War II codebreaker, was one of the most important and influential thinkers of the twentieth century. This volume presents his key writings that deals with: computational theory, cognitive science, artificial intelligence, and artificial life.
Автор: Gouse Baig Mohammad, S. Shitharth, Sachi Nandan Mohanty, Sirisha Potluri Название: Cloud Analytics for Industry 4.0 ISBN: 3110771497 ISBN-13(EAN): 9783110771497 Издательство: Walter de Gruyter Рейтинг: Цена: 192090.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides research on the state-of-the-art methods for data management in the fourth industrial revolution, with particular focus on cloud.based data analytics for digital manufacturing infrastructures. Innovative techniques and methods for secure, flexible and profi table cloud manufacturing will be gathered to present advanced and specialized research in the selected area.
Автор: Parmanand Astya, Prasenjit Chatterjee, Sudeshna Chakraborty Название: Machine Learning Algorithms for Engineering Applications: Future Trends and Research Directions ISBN: 1685074499 ISBN-13(EAN): 9781685074494 Издательство: Nova Science Рейтинг: Цена: 149940.00 T Наличие на складе: Невозможна поставка. Описание: Machine learning is a vital part of numerous academic and financial applications, in areas ranging from health care and treatment to finding relevant information in social networks. Large organisations thoughtfully apply machine learning algorithms with extensive research teams. The purpose of this book is to provide an intellectual introduction to statistical or machine learning (ML) techniques for those that would not normally be exposed to such approaches during their typical required statistical exercise.
Statistical analysis is an integral part of machine learning and can be described as a form of it, often even utilising well-known and familiar techniques, that has a different focus than traditional analytical practice in applied disciplines. The key notion is that flexible, automatic approaches are used to detect patterns within the data, with a primary focus on making predictions on future data.
This work presents the latest development in the field of computational intelligence to advance Big Data and Cloud Computing concerning applications in medical diagnosis. As forum for academia and professionals it covers state-of-the-art research challenges and issues in the digital information & knowledge management and the concerns along with the solutions adopted in these fields.
Автор: Priyanka Harjule, Azizur Rahman, Basant Название: Computational Statistical Methodologies and Modeling for Artificial Intelligence ISBN: 1032170808 ISBN-13(EAN): 9781032170800 Издательство: Taylor&Francis Рейтинг: Цена: 153120.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence.
It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are:Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial IntelligenceExamines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applicationsExamines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionalsProvides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fieldsIntegrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence
As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
Автор: Mishra Abhishek Название: Machine Learning for IOS Developers ISBN: 1119602874 ISBN-13(EAN): 9781119602873 Издательство: Wiley Рейтинг: Цена: 40120.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner
Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple's ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications.
Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book's clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models--both pre-trained and user-built--with Apple's CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers:
Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics
Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming
Develop skills in data acquisition and modeling, classification, and regression.
Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS)
Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML
Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.
Автор: Rajesh R., Thasleema T. M., Kumar V. Название: Intelligent Computing and Signal Processing ISBN: 8184876912 ISBN-13(EAN): 9788184876918 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 57290.00 T Наличие на складе: Поставка под заказ. Описание: Computer science is a fast-growing field which has now applications across disciplines. AI will never replace human beings, but definitely it will provide all types of necessary support/service in all forms to common man to make their work easier. This book discusses artificial intelligence in detail.
Автор: Ramgopal Kashyap, A.V. Senthil Kumar Название: Challenges and Applications for Implementing Machine Learning in Computer Vision ISBN: 1799801837 ISBN-13(EAN): 9781799801832 Издательство: Mare Nostrum (Eurospan) Цена: 173190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.
Автор: Thomas Heinrich Musiolik, Adrian David Cheok Название: Analyzing future applications of ai, sensors, and robotics in society ISBN: 1799835006 ISBN-13(EAN): 9781799835004 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 152460.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents research exploring the potential uses and future challenges of intelligent technological advancements and their impact in education, finance, politics, business, healthcare, and engineering. The book includes coverage on a broad range of topics, such as neuronal networks, cognitive computing, and e-health.
Автор: Min Wu, Xiaoli Li, Zhenghua Chen Название: Generalization With Deep Learning: For Improvement On Sensing Capability ISBN: 9811218838 ISBN-13(EAN): 9789811218835 Издательство: World Scientific Publishing Рейтинг: Цена: 105600.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing.
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