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Languages : en
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How big data impacted social media and IoT Big data for business strategy Ethics in big data Data logistics Structured, semi-structured, and unstructured data Challenges with data preparation Visualizing big data Predictive analysis.
Author: Uri Bram
Publisher:
ISBN: 9780995529588
Category : Business & Economics
Languages : en
Pages : 150
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Book Description
If you're a sentient human these days, you've heard people talking of the phenomenal riches promised by the power of big data. Over the past decade or so, the world around us has undergone a staggering transformation, and great things have been promised to anyone able to ride the AI wave.But how exactly do you catch that wave? What does all this mean for you, whether you're an investor choosing among thousands of possible investments, a manager deciding where to allocate your capital, or a student wondering how to ensure there's good work out there for you by the time you graduate?*The Business of Big Data* will show you how to think strategically about the economic impacts of AI, how to complement AI instead of competing against it, how to reap the rewards of the AI revolution, and how to find your place in our brave new data-driven world. Along the way you'll find out how AI is like (and unlike) an ox, why your bank cares how fast you fill in a form, why your car insurer judges you by your email address, and why everything you do is data - from what time you first check your phone in the morning to where you sleep at night.
Author: Mingbo Gong
Publisher: IAP
ISBN: 1641138998
Category : Computers
Languages : en
Pages : 185
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Book Description
Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field. This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.
Author: Marco Iansiti
Publisher: Harvard Business Press
ISBN: 1633697630
Category : Business & Economics
Languages : en
Pages : 175
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Book Description
"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.
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Languages : en
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Book Description
How big data impacted social media and IoT Big data for business strategy Ethics in big data Data logistics Structured, semi-structured, and unstructured data Challenges with data preparation Visualizing big data Predictive analysis.
Author: Anand Deshpande
Publisher: Packt Publishing Ltd
ISBN: 1788476018
Category : Computers
Languages : en
Pages : 371
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Book Description
Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.
Author: Marjorie Mcshane
Publisher: MIT Press
ISBN: 0262045583
Category : Computers
Languages : en
Pages : 449
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Book Description
A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.
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Category :
Languages : en
Pages :
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Book Description
The hype about big data may have peaked several years ago, but big data is far from gone. Instead it forms the foundation for some of today's most exciting technologies. Artificial intelligence (AI), machine learning, and data science rely on big data, or data that-by virtue of its velocity, volume, or variety-can't be easily stored or analyzed with traditional methods. In this nontechnical course, Barton Poulson digs into the topic of big data, explaining how it works and shapes our modern data universe. Barton explains big data's relationship to AI, data science, social media, and the Internet of Things (IoT). He goes over some of the ethical issues behind the use of big data. Plus, he covers techniques involved in analyzing big data, including data mining and predictive analytics.
Author: Viktor Mayer-Schönberger
Publisher: Basic Books
ISBN: 0465093698
Category : Business & Economics
Languages : en
Pages : 239
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Book Description
From the New York Times bestselling author of Big Data, a prediction for how data will revolutionize the market economy and make cash, banks, and big companies obsolete In modern history, the story of capitalism has been a story of firms and financiers. That's all going to change thanks to the Big Data revolution. As Viktor Mayer-Schörger, bestselling author of Big Data, and Thomas Ramge, who writes for The Economist, show, data is replacing money as the driver of market behavior. Big finance and big companies will be replaced by small groups and individual actors who make markets instead of making things: think Uber instead of Ford, or Airbnb instead of Hyatt. This is the dawn of the era of data capitalism. Will it be an age of prosperity or of calamity? This book provides the indispensable roadmap for securing a better future.
Author: Dr.Talluri.Sunil Kumar
Publisher: Leilani Katie Publication
ISBN: 9363489396
Category : Computers
Languages : en
Pages : 207
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Book Description
Dr.Talluri.Sunil Kumar, Professor, CSE-(CyS, DS) and AI&DS, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India. Manmath Nath Das, Assistant Professor, Artificial Intelligence and Data Science (AI & DS), VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India.
Author: Seth Earley
Publisher: LifeTree Media
ISBN: 1928055524
Category : Business & Economics
Languages : en
Pages : 203
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Book Description
Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.
