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Author: Cybellium Ltd
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 375
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Book Description
In a world driven by cutting-edge technology, artificial intelligence (AI) stands at the forefront of innovation. "Becoming an AI Expert" is an illuminating guide that takes readers on a transformative journey, equipping them with the knowledge and skills needed to navigate the dynamic realm of AI and emerge as true experts in the field. About the Book: In this comprehensive handbook, readers will embark on a captivating exploration of AI from its foundational concepts to advanced applications. Authored by leading experts, "Becoming an AI Expert" offers a structured approach to mastering the intricacies of AI, making it an invaluable resource for both novices and aspiring professionals. Key Features: · AI Fundamentals: The book starts with a solid introduction to AI, demystifying complex concepts and terminology. Readers will gain a clear understanding of the building blocks that underpin AI technologies. · Hands-On Learning: Through practical examples, coding exercises, and real-world projects, readers will engage in hands-on learning that deepens their understanding of AI techniques and algorithms. · Problem-Solving Approach: "Becoming an AI Expert" encourages a problem-solving mindset, guiding readers through the process of identifying challenges that AI can address and devising effective solutions. · AI Subfields: From machine learning and deep learning to natural language processing and computer vision, the book provides an overview of key AI subfields, allowing readers to explore specialized areas of interest. · Ethical Considerations: As AI increasingly shapes society, ethical considerations become paramount. The book delves into the ethical implications of AI and equips readers with tools to develop responsible and socially conscious AI solutions. · Cutting-Edge Trends: Readers will stay ahead of the curve by exploring emerging trends such as AI in healthcare, autonomous vehicles, and AI ethics, ensuring they remain at the forefront of AI advancements. · Industry Insights: Featuring interviews and case studies from AI practitioners, "Becoming an AI Expert" offers a glimpse into real-world applications and insights, bridging the gap between theory and practice. Who Should Read This Book: "Becoming an AI Expert" is an essential read for students, professionals, and enthusiasts seeking to build a solid foundation in AI or advance their existing knowledge. Whether you're a computer science student, a software developer, an engineer, or a curious individual passionate about AI, this book serves as a comprehensive guide to becoming proficient in the AI landscape. About the Authors: The authors of "Becoming an AI Expert" are distinguished experts in the field of artificial intelligence. With years of research, industry experience, and academic contributions, they bring a wealth of knowledge to this guide. Their collective expertise ensures that readers receive accurate, up-to-date, and insightful information about AI.
Author: Cybellium Ltd
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 375
Get Book Here
Book Description
In a world driven by cutting-edge technology, artificial intelligence (AI) stands at the forefront of innovation. "Becoming an AI Expert" is an illuminating guide that takes readers on a transformative journey, equipping them with the knowledge and skills needed to navigate the dynamic realm of AI and emerge as true experts in the field. About the Book: In this comprehensive handbook, readers will embark on a captivating exploration of AI from its foundational concepts to advanced applications. Authored by leading experts, "Becoming an AI Expert" offers a structured approach to mastering the intricacies of AI, making it an invaluable resource for both novices and aspiring professionals. Key Features: · AI Fundamentals: The book starts with a solid introduction to AI, demystifying complex concepts and terminology. Readers will gain a clear understanding of the building blocks that underpin AI technologies. · Hands-On Learning: Through practical examples, coding exercises, and real-world projects, readers will engage in hands-on learning that deepens their understanding of AI techniques and algorithms. · Problem-Solving Approach: "Becoming an AI Expert" encourages a problem-solving mindset, guiding readers through the process of identifying challenges that AI can address and devising effective solutions. · AI Subfields: From machine learning and deep learning to natural language processing and computer vision, the book provides an overview of key AI subfields, allowing readers to explore specialized areas of interest. · Ethical Considerations: As AI increasingly shapes society, ethical considerations become paramount. The book delves into the ethical implications of AI and equips readers with tools to develop responsible and socially conscious AI solutions. · Cutting-Edge Trends: Readers will stay ahead of the curve by exploring emerging trends such as AI in healthcare, autonomous vehicles, and AI ethics, ensuring they remain at the forefront of AI advancements. · Industry Insights: Featuring interviews and case studies from AI practitioners, "Becoming an AI Expert" offers a glimpse into real-world applications and insights, bridging the gap between theory and practice. Who Should Read This Book: "Becoming an AI Expert" is an essential read for students, professionals, and enthusiasts seeking to build a solid foundation in AI or advance their existing knowledge. Whether you're a computer science student, a software developer, an engineer, or a curious individual passionate about AI, this book serves as a comprehensive guide to becoming proficient in the AI landscape. About the Authors: The authors of "Becoming an AI Expert" are distinguished experts in the field of artificial intelligence. With years of research, industry experience, and academic contributions, they bring a wealth of knowledge to this guide. Their collective expertise ensures that readers receive accurate, up-to-date, and insightful information about AI.
Author: Jeremy Howard
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624
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Book Description
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Author: Mo Gawdat
Publisher: Bluebird
ISBN: 9781529077650
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
A Sunday Times Business Book of the Year. Scary Smart will teach you how to navigate the scary and inevitable intrusion of Artificial Intelligence, with an accessible blueprint for creating a harmonious future alongside AI. From Mo Gawdat, the former Chief Business Officer at Google [X] and bestselling author of Solve for Happy. Technology is putting our humanity at risk to an unprecedented degree. This book is not for engineers who write the code or the policy makers who claim they can regulate it. This is a book for you. Because, believe it or not, you are the only one that can fix it. - Mo Gawdat Artificial intelligence is smarter than humans. It can process information at lightning speed and remain focused on specific tasks without distraction. AI can see into the future, predict outcomes and even use sensors to see around physical and virtual corners. So why does AI frequently get it so wrong and cause harm? The answer is us: the human beings who write the code and teach AI to mimic our behaviour. Scary Smart explains how to fix the current trajectory now, to make sure that the AI of the future can preserve our species. This book offers a blueprint, pointing the way to what we can do to safeguard ourselves, those we love, and the planet itself. 'No one ever regrets reading anything Mo Gawdat has written.' - Emma Gannon, author of The Multi-Hyphen Method and host of the podcast Ctrl Alt Delete
Author: Kai-Fu Lee
Publisher: Harper Business
ISBN: 132854639X
Category : Business & Economics
Languages : en
Pages : 275
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Book Description
AI Superpowers is Kai-Fu Lee's New York Times and USA Today bestseller about the American-Chinese competition over the future of artificial intelligence.
Author: Masato Hagiwara
Publisher: Simon and Schuster
ISBN: 1617296422
Category : Computers
Languages : en
Pages : 334
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Book Description
Voice assistants, automated customer service agents, and other cutting-edge human-to-computer interactions rely on accurately interpreting language as it is written and spoken. Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you''ll explore the core tools and techniques required to build a huge range of powerful NLP apps. about the technology Natural language processing is the part of AI dedicated to understanding and generating human text and speech. NLP covers a wide range of algorithms and tasks, from classic functions such as spell checkers, machine translation, and search engines to emerging innovations like chatbots, voice assistants, and automatic text summarization. Wherever there is text, NLP can be useful for extracting meaning and bridging the gap between humans and machines. about the book Real-world Natural Language Processing teaches you how to create practical NLP applications using Python and open source NLP libraries such as AllenNLP and Fairseq. In this practical guide, you''ll begin by creating a complete sentiment analyzer, then dive deep into each component to unlock the building blocks you''ll use in all different kinds of NLP programs. By the time you''re done, you''ll have the skills to create named entity taggers, machine translation systems, spelling correctors, and language generation systems. what''s inside Design, develop, and deploy basic NLP applications NLP libraries such as AllenNLP and Fairseq Advanced NLP concepts such as attention and transfer learning about the reader Aimed at intermediate Python programmers. No mathematical or machine learning knowledge required. about the author Masato Hagiwara received his computer science PhD from Nagoya University in 2009, focusing on Natural Language Processing and machine learning. He has interned at Google and Microsoft Research, and worked at Baidu Japan, Duolingo, and Rakuten Institute of Technology. He now runs his own consultancy business advising clients, including startups and research institutions.
Author: Denis Rothman
Publisher: Packt Publishing Ltd
ISBN: 1800202768
Category : Computers
Languages : en
Pages : 455
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Book Description
Resolve the black box models in your AI applications to make them fair, trustworthy, and secure. Familiarize yourself with the basic principles and tools to deploy Explainable AI (XAI) into your apps and reporting interfaces. Key FeaturesLearn explainable AI tools and techniques to process trustworthy AI resultsUnderstand how to detect, handle, and avoid common issues with AI ethics and biasIntegrate fair AI into popular apps and reporting tools to deliver business value using Python and associated toolsBook Description Effectively translating AI insights to business stakeholders requires careful planning, design, and visualization choices. Describing the problem, the model, and the relationships among variables and their findings are often subtle, surprising, and technically complex. Hands-On Explainable AI (XAI) with Python will see you work with specific hands-on machine learning Python projects that are strategically arranged to enhance your grasp on AI results analysis. You will be building models, interpreting results with visualizations, and integrating XAI reporting tools and different applications. You will build XAI solutions in Python, TensorFlow 2, Google Cloud’s XAI platform, Google Colaboratory, and other frameworks to open up the black box of machine learning models. The book will introduce you to several open-source XAI tools for Python that can be used throughout the machine learning project life cycle. You will learn how to explore machine learning model results, review key influencing variables and variable relationships, detect and handle bias and ethics issues, and integrate predictions using Python along with supporting the visualization of machine learning models into user explainable interfaces. By the end of this AI book, you will possess an in-depth understanding of the core concepts of XAI. What you will learnPlan for XAI through the different stages of the machine learning life cycleEstimate the strengths and weaknesses of popular open-source XAI applicationsExamine how to detect and handle bias issues in machine learning dataReview ethics considerations and tools to address common problems in machine learning dataShare XAI design and visualization best practicesIntegrate explainable AI results using Python modelsUse XAI toolkits for Python in machine learning life cycles to solve business problemsWho this book is for This book is not an introduction to Python programming or machine learning concepts. You must have some foundational knowledge and/or experience with machine learning libraries such as scikit-learn to make the most out of this book. Some of the potential readers of this book include: Professionals who already use Python for as data science, machine learning, research, and analysisData analysts and data scientists who want an introduction into explainable AI tools and techniquesAI Project managers who must face the contractual and legal obligations of AI Explainability for the acceptance phase of their applications
Author: Alex Castrounis
Publisher: "O'Reilly Media, Inc."
ISBN: 1492036528
Category :
Languages : en
Pages : 316
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Book Description
If youâ??re an executive, manager, or anyone interested in leveraging AI within your organization, this is your guide. Youâ??ll understand exactly what AI is, learn how to identify AI opportunities, and develop and execute a successful AI vision and strategy. Alex Castrounis,founder and CEO of Why of AI, Northwestern University Adjunct, advisor, and former IndyCar engineer and data scientist, examines the value of AI and shows you how to develop an AI vision and strategy that benefits both people and business. AI is exciting, powerful, and game changingâ??but too many AI initiatives end in failure. With this book, youâ??ll explore the risks, considerations, trade-offs, and constraints for pursuing an AI initiative. Youâ??ll learn how to create better human experiences and greater business success through winning AI solutions and human-centered products. Use the bookâ??s AIPB Framework to conduct end-to-end, goal-driven innovation and value creation with AI Define a goal-aligned AI vision and strategy for stakeholders, including businesses, customers, and users Leverage AI successfully by focusing on concepts such as scientific innovation and AI readiness and maturity Understand the importance of executive leadership for pursuing AI initiatives "A must read for business executives and managers interested in learning about AI and unlocking its benefits. Alex Castrounis has simplified complex topics so that anyone can begin to leverage AI within their organization." - Dan Park, GM & Director, Uber "Alex Castrounis has been at the forefront of helping organizations understand the promise of AI and leverage its benefits, while avoiding the many pitfalls that can derail success. In this essential book, he shares his expertise with the rest of us." - Dean Wampler, Ph.D., VP, Fast Data Engineering at Lightbend
Author: Tom Taulli
Publisher: Apress
ISBN: 1484250281
Category : Computers
Languages : en
Pages : 195
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Book Description
Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. Author Tom Taulli provides an engaging, non-technical introduction to important concepts such as machine learning, deep learning, natural language processing (NLP), robotics, and more. In addition to guiding you through real-world case studies and practical implementation steps, Taulli uses his expertise to expand on the bigger questions that surround AI. These include societal trends, ethics, and future impact AI will have on world governments, company structures, and daily life. Google, Amazon, Facebook, and similar tech giants are far from the only organizations on which artificial intelligence has had—and will continue to have—an incredibly significant result. AI is the present and the future of your business as well as your home life. Strengthening your prowess on the subject will prove invaluable to your preparation for the future of tech, and Artificial Intelligence Basics is the indispensable guide that you’ve been seeking. What You Will Learn Study the core principles for AI approaches such as machine learning, deep learning, and NLP (Natural Language Processing)Discover the best practices to successfully implement AI by examining case studies including Uber, Facebook, Waymo, UiPath, and Stitch FixUnderstand how AI capabilities for robots can improve businessDeploy chatbots and Robotic Processing Automation (RPA) to save costs and improve customer serviceAvoid costly gotchasRecognize ethical concerns and other risk factors of using artificial intelligenceExamine the secular trends and how they may impact your business Who This Book Is For Readers without a technical background, such as managers, looking to understand AI to evaluate solutions.
Author: Katharina A. Zweig
Publisher: MIT Press
ISBN: 0262047462
Category : Computers
Languages : en
Pages : 283
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Book Description
An expert offers a guide to where we should use artificial intelligence—and where we should not. Before we know it, artificial intelligence (AI) will work its way into every corner of our lives, making decisions about, with, and for us. Is this a good thing? There’s a tendency to think that machines can be more “objective” than humans—can make better decisions about job applicants, for example, or risk assessments. In Awkward Intelligence, AI expert Katharina Zweig offers readers the inside story, explaining how many levers computer and data scientists must pull for AI’s supposedly objective decision making. She presents the good and the bad: AI is good at processing vast quantities of data that humans cannot—but it’s bad at making judgments about people. AI is accurate at sifting through billions of websites to offer up the best results for our search queries and it has beaten reigning champions in games of chess and Go. But, drawing on her own research, Zweig shows how inaccurate AI is, for example, at predicting whether someone with a previous conviction will become a repeat offender. It’s no better than simple guesswork, and yet it’s used to determine people’s futures. Zweig introduces readers to the basics of AI and presents a toolkit for designing AI systems. She explains algorithms, big data, and computer intelligence, and how they relate to one another. Finally, she explores the ethics of AI and how we can shape the process. With Awkward Intelligence. Zweig equips us to confront the biggest question concerning AI: where we should use it—and where we should not.
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
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Book Description
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
