Products related to Data:
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Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches
Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today.This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner.It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful.By the end of this book, you will understand the fundamentals of AI.Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning
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Learn Autonomous Programming with Python : Utilize Python’s capabilities in artificial intelligence, machine learning, deep learning and robotic process automation
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Food Engineering Automation with Robotics and AI
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Business Intelligence : An Essential Beginner's Guide to BI, Big Data, Artificial Intelligence, Cybersecurity, Machine Learning, Data Science, Data Analytics, Social Media and Internet Marketing
Do you want to learn about business intelligence but don't feel like reading a boring textbook?In the modern business world, the pace of action continues to quicken. Businesses need to be able to get actionable insights from their data in order to make the right decisions to act rapidly and effectively.In this book, you will be introduced to the concept of business intelligence. Business intelligence is closely connected to data, and so as part of our journey, we are going to see how modern companies are using big data, together with artificial intelligence, machine learning, and pattern recognition in order to build systems of data-driven decision making.After we get a handle on what business intelligence is, we will learn how it ties together with the next computer revolution (happening right before our eyes). We will discuss the use of artificial intelligence, machine learning, and pattern recognition to retrieve insights from the large amounts of data that companies are routinely collecting, storing, and using.We will also explore the roles that social media and internet marketing are playing in the growth of business intelligence, and how companies like Facebook are helping other companies act on data in powerful ways.Here's just a tiny fraction of what you'll discover:An Introduction to BI, Big Data, AI, and More,An Overview of Business Intelligence,BI and AI,BI and Big Data,BI And Machine Learning,Data Science,Cybersecurity,BI and Data Mining,BI and Social Media,BI and Internet Marketing,And much much more!,So if you want to learn more about Business Intelligence, click the “add to cart” button!
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Which programming language is used for robotics and artificial intelligence?
Python is commonly used for robotics and artificial intelligence due to its simplicity, readability, and extensive libraries for machine learning and robotics. It is also known for its flexibility and ease of integration with hardware, making it a popular choice for developing robotics and AI applications. Additionally, Python's strong community support and active development make it a suitable language for these rapidly evolving fields.
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Is machine learning already artificial intelligence?
Machine learning is a subset of artificial intelligence. It involves training a machine to learn from data and make predictions or decisions without being explicitly programmed to do so. Artificial intelligence, on the other hand, encompasses a broader range of technologies and applications that enable machines to perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, and solving problems. While machine learning is an important component of artificial intelligence, AI also includes other techniques such as natural language processing, computer vision, and robotics.
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What do Data Science and Data Engineering mean?
Data Science involves extracting insights and knowledge from data using various techniques such as statistics, machine learning, and data visualization. Data Scientists are responsible for analyzing and interpreting complex data sets to inform business decisions and solve problems. Data Engineering, on the other hand, focuses on the design and construction of systems for collecting, storing, and processing data. Data Engineers build and maintain the infrastructure that enables data to be accessed and utilized by Data Scientists and other stakeholders. They are also responsible for ensuring the reliability, scalability, and efficiency of data pipelines and storage systems.
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Would you use artificial AI data?
As an AI assistant, I do not have personal preferences or the ability to use data. However, the use of artificial AI data can be beneficial in certain scenarios where real data is limited or unavailable. It can help in training AI models, testing algorithms, and simulating different scenarios. However, it is important to ensure that the artificial data accurately represents the real-world data to avoid biases or inaccuracies in the AI system's performance.
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Artificial Intelligence and Learning Futures : Critical Narratives of Technology and Imagination in Higher Education
Artificial Intelligence and Learning Futures: Critical Narratives of Technology and Imagination in Higher Education explores the implications of artificial intelligence’s adoption in higher education and the challenges to building sustainable instead of dystopic schooling.As AI becomes integral to both pedagogy and profitability in today’s colleges and universities, a critical discourse on these systems and algorithms is urgently needed to push back against their potential to enable surveillance, control, and oppression.This book examines the development, risks, and opportunities inherent to AI in education and curriculum design, the problematic ideological assumptions of intelligence and technology, and the evidence base and ethical imagination required to responsibly implement these learning technologies in a way that ensures quality and sustainability.Leaders, administrators, and faculty as well as technologists and designers will find these provocative and accessible ideas profoundly applicable to their research, decision-making, and concerns.
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The Ultimate Modern Guide to Artificial Intelligence : Including Machine Learning, Deep Learning, IoT, Data Science, Robotics, The Future of Jobs, Required Upskilling and Intelligent Industries
This book is your ultimate guide to understanding the revolutionary technology of Artificial Intelligence (AI).This book covers everything from the basics of AI to its profound impact on various industries, such as healthcare, transportation, banking, and entertainment.You will discover the endless possibilities of AI and how it is changing our lives for the better. The book begins with an introduction to AI and its significance in the modern world.You will learn about the various applications of AI, including speech recognition assistants, image recognition, and biometric data analysis.This will give you a comprehensive understanding of how AI is used in our daily lives and the different industries benefiting from its advancements. In the following chapters, you will delve deeper into the workings of AI, machine learning, deep learning, neural networks, and natural language generation.The book explains how these technologies function and how they are applied in real-life scenarios.You will also gain insights into the differences between human and machine intelligence, providing a holistic understanding of AI's capabilities and limitations. Whether you are a business decision-maker, an IT professional, or someone who is merely interested in the impact of AI on the world, this book is a must-read.With its easy-to-understand language and numerous examples, it empowers you to comprehend the complex technology of AI and be part of the conversation shaping our future.
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Advances in Robotics and Artificial Intelligence
The reality of autonomous machines with artificial intelligence is becoming more real every day.The ability of machines to think and learn fascinates everyone, but now even the most reluctant readers have a chance to engage in learning about the history and future of robotics.This book covers everything from the 18th century French automatons to Ada Lovelace and Alan Turing, from self-driving cars and smart homes to assembly and military robots.Each spread is complimented with vivid artwork that further illuminates the accessible, exciting text.
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Artificial Intelligence And Innovation Management
Artificial Intelligence and Innovation Management contributes to the ongoing debate among innovation scholars and practitioners focusing on the potential impact of Artificial Intelligence (AI) on the ways companies and organizations do business, operate and innovate.It considers AI as a source of innovation both in terms of innovation within the field of AI itself (AI innovation) and in terms of how it enables or disrupts innovation in other fields (AI-driven innovation).The book's content is driven by several important conclusions:It is therefore both necessary and timely to explore the different aspects of the relationship between AI and IM.The contributors to this book include both scholars and practitioners from multiple countries and different types of institutions.They were selected based on their ability to provide a relevant distinctive perspective on the relationship between AI and IM; the degree of their professional engagement with the field; their ability to contribute to the thematic and contextual diversity of the contributions; and their ability to provide actionable insights for both innovation scholars and practitioners.Helena Blackbright (Mälardalen University, Sweden) and Stoyan Tanev (Carleton University, Canada) are chairing the Special Interest Group on AI and IM at the International Society for Professional Innovation Management (https://www.ispim-innovation.com/).
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What are interesting application areas in the fields of digitalization, big data, and artificial intelligence?
Some interesting application areas in the fields of digitalization, big data, and artificial intelligence include healthcare, finance, and transportation. In healthcare, these technologies can be used for personalized medicine, disease prediction, and improving patient care. In finance, they can be utilized for fraud detection, risk assessment, and algorithmic trading. In transportation, they can help optimize routes, reduce traffic congestion, and enhance autonomous driving systems. These application areas showcase the potential of digitalization, big data, and artificial intelligence to revolutionize various industries and improve efficiency and decision-making processes.
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What are interesting application areas in the field of digitization, big data, and artificial intelligence?
Some interesting application areas in the field of digitization, big data, and artificial intelligence include healthcare, where these technologies can be used for medical imaging analysis, patient data management, and drug discovery. Another area is in finance, where they can be used for fraud detection, risk assessment, and algorithmic trading. Additionally, in transportation, these technologies can be applied for traffic management, autonomous vehicles, and predictive maintenance of infrastructure. Finally, in retail, they can be used for personalized marketing, demand forecasting, and supply chain optimization.
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How difficult is a study of robotics and automation?
The study of robotics and automation can be challenging due to its interdisciplinary nature, requiring knowledge in fields such as mechanical engineering, electrical engineering, computer science, and control systems. Additionally, the rapid advancements in technology and the need to stay updated with the latest developments can add to the complexity of the study. However, with dedication, problem-solving skills, and a strong foundation in mathematics and physics, students can overcome these challenges and excel in the field of robotics and automation.
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How could society of tomorrow look like as artificial intelligence and automation continue to advance?
As artificial intelligence and automation continue to advance, the society of tomorrow could see significant changes in various aspects of life. There may be increased efficiency and productivity in industries, leading to a shift in the job market and the need for new skill sets. There could also be advancements in healthcare, transportation, and communication, improving the overall quality of life. However, there may also be concerns about job displacement and the ethical implications of AI, leading to a need for new regulations and policies to ensure a fair and equitable society. Overall, the society of tomorrow could be more technologically advanced, but it will also require careful consideration of the social and ethical impacts of these advancements.
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