Download or read book Introducing MLOps written by Mark Treveil and published by "O'Reilly Media, Inc.". This book was released on 2020-11-30 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized

Download or read book Responsible AI in the Enterprise written by Adnan Masood and published by Packt Publishing Ltd. This book was released on 2023-07-31 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfalls Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn ethical AI principles, frameworks, and governance Understand the concepts of fairness assessment and bias mitigation Introduce explainable AI and transparency in your machine learning models Book DescriptionResponsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations. By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.What you will learn Understand explainable AI fundamentals, underlying methods, and techniques Explore model governance, including building explainable, auditable, and interpretable machine learning models Use partial dependence plot, global feature summary, individual condition expectation, and feature interaction Build explainable models with global and local feature summary, and influence functions in practice Design and build explainable machine learning pipelines with transparency Discover Microsoft FairLearn and marketplace for different open-source explainable AI tools and cloud platforms Who this book is for This book is for data scientists, machine learning engineers, AI practitioners, IT professionals, business stakeholders, and AI ethicists who are responsible for implementing AI models in their organizations.

Download or read book Trustworthy AI written by Beena Ammanath and published by John Wiley & Sons. This book was released on 2022-03-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI.

Download or read book OECD Business and Finance Outlook 2021 AI in Business and Finance written by OECD and published by OECD Publishing. This book was released on 2021-09-24 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: The OECD Business and Finance Outlook is an annual publication that presents unique data and analysis on the trends, both positive and negative, that are shaping tomorrow’s world of business, finance and investment.

Download or read book The Future Computed written by and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Detecting Regime Change in Computational Finance written by Jun Chen and published by CRC Press. This book was released on 2020-09-14 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.

Download or read book Responsible AI and Ethical Issues for Businesses and Governments written by Bistra Vassileva and published by . This book was released on 2020-09 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is aimed at scholars and practitioners who want to widen their understanding of artificial intelligence out of the 'narrow' technical perspective to a more broad viewpoint that embraces the links between AI theory, practice, and policy"--

Download or read book Demystifying AI for the Enterprise written by Prashant Natarajan and published by CRC Press. This book was released on 2021-12-30 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products. There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI. This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes. AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction.

Download or read book The AI Organization written by David Carmona and published by O'Reilly Media. This book was released on 2019-11-12 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Much in the same way that software transformed business in the past two decades, AI is set to redefine organizations and entire industries. Just as every company is a software company today, every company will soon be an AI company. This practical guide explains how business and technical leaders can embrace this new breed of organization. Based on real customer experience, Microsoft’s David Carmona covers the journey necessary to become an AI Organization—from applying AI in your business today to the deep transformation that can empower your organization to redefine the industry. You'll learn the core concepts of AI as they are applied to real business, explore and prioritize the most appropriate use cases for AI in your company, and drive the organizational and cultural change needed to transform your business with AI.

Download or read book Responsible AI written by Olivia Gambelin and published by Kogan Page Publishers. This book was released on 2024-06-03 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Responsible AI is a guide to how business leaders can develop and implement a robust and responsible AI strategy for their organizations. Responsible AI has rapidly transitioned to a strategic priority for leaders and organizations worldwide. Responsible AI guides readers step-by-step through the process of establishing robust yet manageable ethical AI initiatives for any size organization, outlining the three core pillars of building a responsible AI strategy: people, process and technology. It provides the insight and guidance needed to help leaders fully understand the technical and commercial potential of ethics in AI while also covering the operations and strategy needed to support implementation. Responsible AI breaks down what it means to use ethics and values as a modern-day decision-making tool in the design and development of AI. It conceptually covers both how ethics can be used to identify risks and establish safeguards in the development of AI and how to use ethics-by-design methods to stimulate AI innovation. It also covers the different considerations for large enterprises and SMEs and discusses the role of the AI ethicist. It is supported by practical case studies from organizations such as IKEA, Nvidia, Rolls-Royce and NatWest Group.

Download or read book Responsible AI and Ethical Issues for Businesses and Governments written by Vassileva, Bistra and published by IGI Global. This book was released on 2020-10-16 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research surrounding artificial intelligence (AI) is vast and quite diverse in both its applied and theoretical fields. AI tools and techniques, such as machine learning, data mining, neural networks, and advanced analytics, are evolving at a high speed, creating a consistent need for updated research. This is especially relevant with frequent developments for the application of AI technology in many science and industry sectors. This rapid expansion created a need for research that focuses on the questions surrounding the development of AI such as ethical issues, responsible AI methods and applications, and its widespread implementation. Within the answers to these questions is the prevailing notion that AI should be accountable, explainable, transparent, and fair for all organizations and individuals. Responsible AI and Ethical Issues for Businesses and Governments widens the understanding of AI outside of the “narrow” technical perspective to a broader viewpoint that embraces the links between AI theory, practice, and policy. The chapters in this book discuss the basic philosophical and conceptual foundations of AI and explores the responsible application of AI tools and methods, the moral aspects of AI, practical issues, and responsible AI implementation across a range of industries. While highlighting topics that include digital transformation, ethical competence, information literacy in AI, and the interaction between AI and humans, this book is ideally designed for IT specialists, technology developers, technologists, ethicists, practitioners, stakeholders, academicians, students, and researchers who are interested in learning more about the ethical and responsible use of AI.

Download or read book Demystifying AI for the Enterprise written by Prashant Natarajan and published by CRC Press. This book was released on 2021-12-30 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products. There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI. This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes. AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction.

Download or read book Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry written by Chkoniya, Valentina and published by IGI Global. This book was released on 2021-06-25 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.

Download or read book Responsible Artificial Intelligence written by Virginia Dignum and published by Springer Nature. This book was released on 2019-11-04 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens.

Download or read book Real World AI written by Alyssa Simpson Rochwerger and published by Lioncrest Publishing. This book was released on 2021-03-16 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can you successfully deploy AI? When AI works, it's nothing short of brilliant, helping companies make or save tremendous amounts of money while delighting customers on an unprecedented scale. When it fails, the results can be devastating. Most AI models never make it out of testing, but those failures aren't random. This practical guide to deploying AI lays out a human-first, responsible approach that has seen more than three times the success rate when compared to the industry average. In Real World AI, Alyssa Simpson Rochwerger and Wilson Pang share dozens of AI stories from startups and global enterprises alike featuring personal experiences from people who have worked on global AI deployments that impact billions of people every day.  AI for business doesn't have to be overwhelming. Real World AI uses plain language to walk you through an AI approach that you can feel confident about-for your business and for your customers.

Download or read book Human Machine written by Paul R. Daugherty and published by Harvard Business Press. This book was released on 2018-03-20 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.

Download or read book The AI Book written by Ivana Bartoletti and published by John Wiley & Sons. This book was released on 2020-06-29 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important