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Author: N., Ambika
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 308
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Book Description
Organizations worldwide grapple with the complexities of incorporating machine learning into their business models while ensuring sustainability. Decision-makers, data scientists, and business executives face the challenge of navigating this terrain to drive innovation and maintain a competitive edge. Building Business Models with Machine Learning provides a comprehensive solution, offering practical insights and strategies for integrating machine learning into organizational plans. By bridging the gap between theory and practice, we empower readers to leverage machine learning effectively, enabling them to develop resilient and flexible business models. The book serves as a vital resource for those seeking to understand the nuances of sustainable management in a volatile, uncertain, complex, and ambiguous (VUCA) world. It addresses key challenges such as irrational decision-making and the need for adaptive systems in modern business environments. Through a combination of theoretical frameworks and empirical research findings, our book equips readers with the knowledge and tools needed to navigate these challenges successfully. Whether you are a seasoned professional, a postgraduate MBA program, or a managerial sciences student, this book offers invaluable insights that will significantly enhance your understanding and application of machine learning in business models.
Author: N., Ambika
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 308
Get Book Here
Book Description
Organizations worldwide grapple with the complexities of incorporating machine learning into their business models while ensuring sustainability. Decision-makers, data scientists, and business executives face the challenge of navigating this terrain to drive innovation and maintain a competitive edge. Building Business Models with Machine Learning provides a comprehensive solution, offering practical insights and strategies for integrating machine learning into organizational plans. By bridging the gap between theory and practice, we empower readers to leverage machine learning effectively, enabling them to develop resilient and flexible business models. The book serves as a vital resource for those seeking to understand the nuances of sustainable management in a volatile, uncertain, complex, and ambiguous (VUCA) world. It addresses key challenges such as irrational decision-making and the need for adaptive systems in modern business environments. Through a combination of theoretical frameworks and empirical research findings, our book equips readers with the knowledge and tools needed to navigate these challenges successfully. Whether you are a seasoned professional, a postgraduate MBA program, or a managerial sciences student, this book offers invaluable insights that will significantly enhance your understanding and application of machine learning in business models.
Author: Bert Langa
Publisher: Innovation
ISBN: 9781980887157
Category : Business & Economics
Languages : en
Pages : 70
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Book Description
Every few years, there is a technological trend that leads to the creation of thousands of startups and/or new businesses. At present, we can say without any doubt that one of these trends is Machine Learning (Artificial Intelligence).There is a very powerful reason that this is happening. Currently, we are transitioning from the industrial economy born in the late nineteenth century to a new digital economy centered on data. In this data economy, the success of an organization depends to a large extent on how it uses data to make better decisions. Therefore, leading companies are starting to use their data and Machine Learning algorithms to improve their business processes and, consequently, their results.To put it in context, McKinsey (one of the leading Management Consulting companies worldwide) tells us that "Tech giants including Baidu and Google are spending between $20B to $30B on AI, with 90% of this spent on R&D and deployment, and 10% on AI acquisitions".Amazing, right? Can you imagine capturing one-thousandth of these investments with a new startup or a new business model? Well, that is the main objective of this course: explaining the key concepts of Machine Learning in a very practical way, along with the methods needed for creating disruptive Business Models based on said Tech Trend.That way, you can take advantage of this tremendous opportunity and become a successful businessperson or entrepreneur.
Author: Emmanuel Ameisen
Publisher: "O'Reilly Media, Inc."
ISBN: 1492045063
Category : Computers
Languages : en
Pages : 243
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Book Description
Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers—including experienced practitioners and novices alike—will learn the tools, best practices, and challenges involved in building a real-world ML application step by step. Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies. This book will help you: Define your product goal and set up a machine learning problem Build your first end-to-end pipeline quickly and acquire an initial dataset Train and evaluate your ML models and address performance bottlenecks Deploy and monitor your models in a production environment
Author: Doug Hudgeon
Publisher: Simon and Schuster
ISBN: 1638353972
Category : Computers
Languages : en
Pages : 426
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Book Description
Summary Imagine predicting which customers are thinking about switching to a competitor or flagging potential process failures before they happen Think about the benefits of forecasting tedious business processes and back-office tasks Envision quickly gauging customer sentiment from social media content (even large volumes of it). Consider the competitive advantage of making decisions when you know the most likely future events Machine learning can deliver these and other advantages to your business, and it’s never been easier to get started! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Machine learning can deliver huge benefits for everyday business tasks. With some guidance, you can get those big wins yourself without complex math or highly paid consultants! If you can crunch numbers in Excel, you can use modern ML services to efficiently direct marketing dollars, identify and keep your best customers, and optimize back office processes. This book shows you how. About the book Machine Learning for Business teaches business-oriented machine learning techniques you can do yourself. Concentrating on practical topics like customer retention, forecasting, and back office processes, you’ll work through six projects that help you form an ML-for-business mindset. To guarantee your success, you’ll use the Amazon SageMaker ML service, which makes it a snap to turn your questions into results. What's inside Identifying tasks suited to machine learning Automating back office processes Using open source and cloud-based tools Relevant case studies About the reader For technically inclined business professionals or business application developers. About the author Doug Hudgeon and Richard Nichol specialize in maximizing the value of business data through AI and machine learning for companies of any size. Table of Contents: PART 1 MACHINE LEARNING FOR BUSINESS 1 ¦ How machine learning applies to your business PART 2 SIX SCENARIOS: MACHINE LEARNING FOR BUSINESS 2 ¦ Should you send a purchase order to a technical approver? 3 ¦ Should you call a customer because they are at risk of churning? 4 ¦ Should an incident be escalated to your support team? 5 ¦ Should you question an invoice sent by a supplier? 6 ¦ Forecasting your company’s monthly power usage 7 ¦ Improving your company’s monthly power usage forecast PART 3 MOVING MACHINE LEARNING INTO PRODUCTION 8 ¦ Serving predictions over the web 9 ¦ Case studies
Author: Ekaba Bisong
Publisher: Apress
ISBN: 1484244702
Category : Computers
Languages : en
Pages : 703
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Book Description
Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers
Author: Harvard Business Review
Publisher: HBR Insights
ISBN: 9781633697898
Category : Business & Economics
Languages : en
Pages : 160
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Book Description
Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.
Author: Marco Iansiti
Publisher: Harvard Business Press
ISBN: 1633697630
Category : Business & Economics
Languages : en
Pages : 181
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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.
Author: Mariusz Soltanifar
Publisher: Springer Nature
ISBN: 3030539148
Category : Business & Economics
Languages : en
Pages : 339
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Book Description
This open access book explores the global challenges and experiences related to digital entrepreneurial activities, using carefully selected examples from leading companies and economies that shape world business today and tomorrow. Digital entrepreneurship and the companies steering it have an enormous global impact; they promise to transform the business world and change the way we communicate with each other. These companies use digitalization and artificial intelligence to enhance the quality of decisions and augment their business and customer operations. This book demonstrates how cloud services are continuing to evolve; how cryptocurrencies are traded in the banking industry; how platforms are created to commercialize business, and how, taken together, these developments provide new opportunities in the digitalized era. Further, it discusses a wide range of digital factors changing the way businesses operate, including artificial intelligence, chatbots, voice search, augmented and virtual reality, as well as cyber threats and data privacy management. “Digitalization mirrors the Industrial Revolution’s impact. This book provides a complement of perspectives on the opportunities emanating from such a deep seated change in our economy. It is a comprehensive collection of thought leadership mapped into a very useful framework. Scholars, digital entrepreneurs and practitioners will benefit from this timely work.” Gina O’Connor, Professor of Innovation Management at Babson College, USA “This book defines and delineates the requirements for companies to enable their businesses to succeed in a post-COVID19 world. This book deftly examines how to accomplish and achieve digital entrepreneurship by leveraging cloud computing, AI, IoT and other critical technologies. This is truly a unique “must-read” book because it goes beyond theory and provides practical examples.” Charlie Isaacs, CTO of Customer Connection at Salesforce.com, USA "This book provides digital entrepreneurs useful guidance identifying, validating and building their venture. The international authors developed new perspectives on digital entrepreneurship that can support to create impact ventures.” Felix Staeritz, CEO FoundersLane, Member of the World Economic Forum Digital Leaders Board and bestselling author of FightBack, Germany
Author: Barry Libert
Publisher: Harvard Business Review Press
ISBN: 163369206X
Category : Business & Economics
Languages : en
Pages : 247
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Book Description
Pivot your organization toward a more scalable and profitable business model. Digital networks are changing all the rules of business. New, scalable, digitally networked business models, like those of Amazon, Google, Uber, and Airbnb, are affecting growth, scale, and profit potential for companies in every industry. But this seismic shift isn’t unique to digital start-ups and tech superstars. Digital transformation is affecting every business sector, and as investor capital, top talent, and customers shift toward network-centric organizations, the performance gap between early and late adopters is widening. So the question isn’t whether your organization needs to change, but when and how much. The Network Imperative is a call to action for managers and executives to embrace network-based business models. The benefits are indisputable: companies that leverage digital platforms to co-create and share value with networks of employees, customers, and suppliers are fast outpacing the market. These companies, or network orchestrators, grow faster, scale with lower marginal cost, and generate the highest revenue multipliers. Supported by research that covers fifteen hundred companies, authors Barry Libert, Megan Beck, and Jerry Wind guide leaders and investors through the ten principles that all organizations can use to grow and profit regardless of their industry. They also share a five-step process for pivoting an organization toward a more scalable and profitable business model. The Network Imperative, brimming with compelling case studies and actionable advice, provides managers with what they really need: new tools and frameworks to generate unprecedented value in a rapidly changing age.
Author: Bernard Marr
Publisher: John Wiley & Sons
ISBN: 1119548985
Category : Business & Economics
Languages : en
Pages : 220
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Book Description
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.
