Ai Foundations Of Gpt

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AI Foundations of GPT

Author : Jon Adams
Publisher : Green Mountain Computing
ISBN 13 :
Total Pages : 143 pages
Book Rating : 4./5 ( download)

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Book Synopsis AI Foundations of GPT by : Jon Adams

Download or read book AI Foundations of GPT written by Jon Adams and published by Green Mountain Computing. This book was released on with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into the heart of artificial intelligence with "AI Foundations of GPT," a groundbreaking book that charts the journey of Generative Pre-trained Transformers (GPT) from their conceptual inception to their role as cornerstones of modern AI applications. This meticulously crafted text serves as both a historical narrative and a forward-looking discussion, exploring the myriad ways in which GPT technology is reshaping our digital landscape. Key Features: Comprehensive Coverage: From the AI revolution to the future of GPT, each chapter is dedicated to a different facet of GPT technology, ensuring readers gain a well-rounded understanding of its complexities and capabilities. Accessible Explanations: Designed to cater to both AI aficionados and newcomers, the book explains the technical underpinnings of GPT models in an engaging and understandable manner. Future-Oriented: Offers a peek into the potential advancements and challenges that lie ahead for GPT technology, encouraging readers to ponder its implications for society and industry. Chapters: The AI Revolution: An overview of how artificial intelligence has evolved, setting the stage for the emergence of GPT. Understanding GPT: Breaks down the basics of Generative Pre-trained Transformers, explaining what they are and why they matter. The Mechanics of GPT: Delves into the technical aspects of how GPT models work, from algorithms to neural networks. Training GPT Models: Discusses the process of training GPT models, highlighting the resources and methodologies involved. Applications of GPT: Explores the diverse applications of GPT in various fields such as literature, customer service, and software development. Ethical Considerations: Examines the ethical dilemmas and considerations surrounding the use of GPT technology. The Business of GPT: Analyzes the economic landscape of GPT, including its impact on industries and business models. Limitations and Challenges: Acknowledges the limitations of current GPT models and the challenges facing their development. The Future of GPT: Speculates on the future advancements of GPT technology and its potential societal impacts. Whether you're deeply embedded in the world of AI or simply curious about the technologies shaping our future, "AI Foundations of GPT" offers a rich, insightful exploration of one of the most significant developments in artificial intelligence. Embark on this journey to understand not just the mechanics of GPT, but its profound implications on our world.

AI Foundations of Generative AI

Author : Jon Adams
Publisher : Green Mountain Computing
ISBN 13 :
Total Pages : 136 pages
Book Rating : 4./5 ( download)

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Book Synopsis AI Foundations of Generative AI by : Jon Adams

Download or read book AI Foundations of Generative AI written by Jon Adams and published by Green Mountain Computing. This book was released on with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into the captivating world of Generative AI with "AI Foundations of Generative AI," a groundbreaking exploration at the crossroads of creativity and technology. This enlightening book serves as your comprehensive guide through the burgeoning field of Generative AI, where machines wield the power of creativity to produce art, music, literature, and more. Authored by leading experts in the field, this book demystifies the complex algorithms behind AI's ability to emulate human creativity, offering readers a front-row seat to the future of digital innovation. Key Features: Engaging Content: Written in an accessible style, free from daunting jargon, making complex concepts approachable for all readers. Interactive Exercises: Hands-on activities to deepen understanding of AI principles. Ethical Considerations: Insightful discussions on the moral implications of virtual influencers, deepfakes, and AI-driven creativity. Chapters Overview: The Digital Composer: Uncover how AI creates symphonies that challenge the works of great composers. Artistic Algorithms: Explore the systems generating visual art indistinguishable from human-created pieces. Wordsmiths of the Digital Age: Delve into how AI crafts poetry and prose with the finesse of human writers. Synthesized Realities: Navigate the creation of hyper-realistic images, videos, and sounds through AI. Virtual Influencers and Moral Codes: Examine the ethical dimensions of AI-driven personalities and content. Data Driven Storytelling: Understand how AI transforms data into compelling narratives and interactive experiences. Chat GPT and Open AI: Gain insights into the organizations and technologies at the forefront of generative AI. Content Tailored by Technology: Discover the future of personalized media and digital environments shaped by AI. Perfect for tech enthusiasts, creative professionals, and anyone curious about the intersection of art and artificial intelligence, "AI Foundations of Generative AI" offers a unique lens through which to view the future of creativity and technology. Whether you're a tech-savvy reader or new to the world of AI, this book promises to enlighten and inspire with its vision of a world where creativity knows no bounds. Embark on a Journey of Discovery: Prepare to be both enlightened and inspired as you explore the limitless possibilities of Generative AI. "AI Foundations of Generative AI" is your ticket to understanding and participating in the future of creative technology.

AI Foundations of Large Language Models

Author : Jon Adams
Publisher : Green Mountain Computing
ISBN 13 :
Total Pages : 137 pages
Book Rating : 4./5 ( download)

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Book Synopsis AI Foundations of Large Language Models by : Jon Adams

Download or read book AI Foundations of Large Language Models written by Jon Adams and published by Green Mountain Computing. This book was released on with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into the fascinating world of artificial intelligence with Jon Adams' groundbreaking book, AI Foundations of Large Language Models. This comprehensive guide serves as a beacon for both beginners and enthusiasts eager to understand the intricate mechanisms behind the digital forces shaping our future. With Adams' expert narration, readers are invited to explore the evolution of language models that have transformed mere strings of code into entities capable of human-like text generation. Key Features: In-depth Exploration: From the initial emergence to the sophisticated development of Large Language Models (LLMs), this book covers it all. Technical Insights: Understand the foundational technology, including neural networks, transformers, and attention mechanisms, that powers LLMs. Practical Applications: Discover how LLMs are being utilized in industry and research, paving the way for future innovations. Ethical Considerations: Engage with the critical discussions surrounding the ethics of LLM development and deployment. Chapters Include: The Emergence of Language Models: An introduction to the genesis of LLMs and their significance. Foundations of Neural Networks: Delve into the neural underpinnings that make it all possible. Transformers and Attention Mechanisms: Unpack the mechanisms that enhance LLM efficiency and accuracy. Training Large Language Models: A guide through the complexities of LLM training processes. Understanding LLMs Text Generation: Insights into how LLMs generate text that rivals human writing. Natural Language Understanding: Explore the advancements in LLMs' comprehension capabilities. Ethics and LLMs: A critical look at the ethical landscape of LLM technology. LLMs in Industry and Research: Real-world applications and the impact of LLMs across various sectors. The Future of Large Language Models: Speculations and predictions on the trajectory of LLM advancements. Whether you're a student, professional, or simply an AI enthusiast, AI Foundations of Large Language Models by Jon Adams offers a riveting narrative filled with insights and foresights. Equip yourself with the knowledge to navigate the burgeoning world of LLMs and appreciate their potential to redefine our technological landscape. Join us on this enlightening journey through the annals of artificial intelligence, where the future of digital communication and creativity awaits.

Zero to AI

Author : Nicolò Valigi
Publisher : Manning Publications
ISBN 13 : 1617296066
Total Pages : 262 pages
Book Rating : 4.6/5 (172 download)

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Book Synopsis Zero to AI by : Nicolò Valigi

Download or read book Zero to AI written by Nicolò Valigi and published by Manning Publications. This book was released on 2020-05-19 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary How can artificial intelligence transform your business? In Zero to AI, you’ll explore a variety of practical AI applications you can use to improve customer experiences, optimize marketing, help you cut costs, and more. In this engaging guide written for business leaders and technology pros alike, authors and AI experts Nicolò Valigi and Gianluca Mauro use fascinating projects, hands-on activities, and real-world explanations to make it clear how your business can benefit from AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology There’s no doubt that artificial intelligence has made some impressive headlines recently, from besting chess and Go grand masters to producing uncanny deep fakes that blur the lines of reality. But what can AI do for you? If you want to understand how AI will impact your business before you invest your time and money, this book is for you. About the book Zero to AI uses clear examples and jargon-free explanations to show the practical benefits of AI. Each chapter explores a real-world case study demonstrating how companies like Google and Netflix use AI to shape their industries. You begin at the beginning, with a primer on core AI concepts and realistic business outcomes. To help you prepare for the transition, the book breaks down a successful AI implementation, including advice on hiring the right team and making decisions about resources, risks, and costs. What's inside Identifying where AI can help your organization Designing an AI strategy Evaluating project scope and business impact Using AI to boost conversion rates, curate content, and analyze feedback Understanding how modern AI works and what it can/can’t do About the reader For anyone who wants to gain an understanding of practical artificial intelligence and learn how to design and develop projects with high business impact. About the author Gianluca Mauro and Nicolò Valigi are the cofounders of AI Academy, a company specializing in AI trainings and consulting. Table of Contents: 1. An introduction to artificial intelligence PART 1 - UNDERSTANDING AI 2. Artificial intelligence for core business data 3. AI for sales and marketing 4. AI for media 5. AI for natural language 6. AI for content curation and community building PART 2 - BUILDING AI 7. Ready—finding AI opportunities 8. Set—preparing data, technology, and people 9. Go—AI implementation strategy 10. What lies ahead

Artificial Intelligence Basics

Author : Tom Taulli
Publisher : Apress
ISBN 13 : 1484250281
Total Pages : 195 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Artificial Intelligence Basics by : Tom Taulli

Download or read book Artificial Intelligence Basics written by Tom Taulli and published by Apress. This book was released on 2019-08-01 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Rebooting AI

Author : Gary Marcus
Publisher : Vintage
ISBN 13 : 1524748269
Total Pages : 288 pages
Book Rating : 4.5/5 (247 download)

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Book Synopsis Rebooting AI by : Gary Marcus

Download or read book Rebooting AI written by Gary Marcus and published by Vintage. This book was released on 2019-09-10 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.

Generative AI Foundations in Python

Author : Carlos Rodriguez
Publisher : Packt Publishing Ltd
ISBN 13 : 1835464912
Total Pages : 190 pages
Book Rating : 4.8/5 (354 download)

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Book Synopsis Generative AI Foundations in Python by : Carlos Rodriguez

Download or read book Generative AI Foundations in Python written by Carlos Rodriguez and published by Packt Publishing Ltd. This book was released on 2024-07-26 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Begin your generative AI journey with Python as you explore large language models, understand responsible generative AI practices, and apply your knowledge to real-world applications through guided tutorials Key Features Gain expertise in prompt engineering, LLM fine-tuning, and domain adaptation Use transformers-based LLMs and diffusion models to implement AI applications Discover strategies to optimize model performance, address ethical considerations, and build trust in AI systems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe intricacies and breadth of generative AI (GenAI) and large language models can sometimes eclipse their practical application. It is pivotal to understand the foundational concepts needed to implement generative AI. This guide explains the core concepts behind -of-the-art generative models by combining theory and hands-on application. Generative AI Foundations in Python begins by laying a foundational understanding, presenting the fundamentals of generative LLMs and their historical evolution, while also setting the stage for deeper exploration. You’ll also understand how to apply generative LLMs in real-world applications. The book cuts through the complexity and offers actionable guidance on deploying and fine-tuning pre-trained language models with Python. Later, you’ll delve into topics such as task-specific fine-tuning, domain adaptation, prompt engineering, quantitative evaluation, and responsible AI, focusing on how to effectively and responsibly use generative LLMs. By the end of this book, you’ll be well-versed in applying generative AI capabilities to real-world problems, confidently navigating its enormous potential ethically and responsibly.What you will learn Discover the fundamentals of GenAI and its foundations in NLP Dissect foundational generative architectures including GANs, transformers, and diffusion models Find out how to fine-tune LLMs for specific NLP tasks Understand transfer learning and fine-tuning to facilitate domain adaptation, including fields such as finance Explore prompt engineering, including in-context learning, templatization, and rationalization through chain-of-thought and RAG Implement responsible practices with generative LLMs to minimize bias, toxicity, and other harmful outputs Who this book is for This book is for developers, data scientists, and machine learning engineers embarking on projects driven by generative AI. A general understanding of machine learning and deep learning, as well as some proficiency with Python, is expected.

Deep Learning for Coders with fastai and PyTorch

Author : Jeremy Howard
Publisher : O'Reilly Media
ISBN 13 : 1492045497
Total Pages : 624 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for Coders with fastai and PyTorch by : Jeremy Howard

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Deep Learning Illustrated

Author : Jon Krohn
Publisher : Addison-Wesley Professional
ISBN 13 : 0135121728
Total Pages : 725 pages
Book Rating : 4.1/5 (351 download)

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Book Synopsis Deep Learning Illustrated by : Jon Krohn

Download or read book Deep Learning Illustrated written by Jon Krohn and published by Addison-Wesley Professional. This book was released on 2019-08-05 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Artificial Intelligence Simplified

Author : Binto George
Publisher : CSTrends LLP
ISBN 13 : 1944708022
Total Pages : 1 pages
Book Rating : 4.9/5 (447 download)

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Book Synopsis Artificial Intelligence Simplified by : Binto George

Download or read book Artificial Intelligence Simplified written by Binto George and published by CSTrends LLP. This book was released on 2016-01-08 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces key Artificial Intelligence (AI) concepts in an easy-to-read format with examples and illustrations. A complex, long, overly mathematical textbook does not always serve the purpose of conveying the basic AI concepts to most people. Someone with basic knowledge in Computer Science can have a quick overview of AI (heuristic searches, genetic algorithms, expert systems, game trees, fuzzy expert systems, natural language processing, super intelligence, etc.) with everyday examples. If you are taking a basic AI course and find the traditional AI textbooks intimidating, you may choose this as a “bridge” book, or as an introductory textbook. For students, there is a lower priced edition (ISBN 978-1944708016) of the same book. Published by CSTrends LLP.

Unsupervised

Author : Daniel Doll-Steinberg
Publisher : John Wiley & Sons
ISBN 13 : 1394209916
Total Pages : 260 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Unsupervised by : Daniel Doll-Steinberg

Download or read book Unsupervised written by Daniel Doll-Steinberg and published by John Wiley & Sons. This book was released on 2023-07-25 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: How a broad range of new immensely powerful technologies is disrupting and transforming every corner of our reality—and why you must act and adapt Unsupervised: Navigating and Influencing a World Controlled by Powerful New Technologies examines the fast-emerging technologies and tools that are already starting to completely revolutionize our world. Beyond that, the book takes an in-depth look at how we have arrived at this dizzying point in our history, who holds the reins of these formidable technologies, mostly without any supervision. It explains why we as business leaders, entrepreneurs, academics, educators, lawmakers, investors or users and all responsible citizens must act now to influence and help oversee the future of a technological world. Quantum computing, artificial intelligence, blockchain, decentralization, virtual and augmented reality, and permanent connectivity are just a few of the technologies and trends considered, but the book delves much deeper, too. You'll find a thorough analysis of energy and medical technologies, as well as cogent predictions for how new tech will redefine your work, your money, your entertainment, your transportation and your home and cities, and what you need to know to harness and prosper from these technologies. Authors Daniel Doll-Steinberg and Stuart Leaf draw on their decades of building and implementing disruptive technologies, investing and deploying funds, and advising business leaders, governments and supranational bodies on change management, the future of work, innovation and disruption, education and the economy to consider how every area of our lives, society, economy and government will likely witness incredible changes in the coming decade. When we look just a bit further into the future, we can see that the task facing us is to completely reinvent life as we know it—work, resources, war, and even humanity itself will undergo redefinition, thanks to these new and emerging tools. In Unsupervised, you'll consider what these redefinitions might look like, and how we as individuals, and part of society, can prevent powerful new technologies from falling into the wrong hands or be built to harm us. Get a primer on the foundational technologies that are reshaping business, pleasure, and life as we know it Learn about the lesser known, yet astonishing, technologies set to revolutionize medicine, agriculture, and beyond Consider the potential impact of new tech across business sectors—and what it means for you Gain the knowledge and inspiration you need to harness your own power and push the future in the direction of good for all of us not just the few Explore the best ways to invest in the changes these technologies of the future will bring about This is a remarkably thorough and comprehensive look at the future of technology and everything it touches. Shining a light on many unsupervised technologies and their unsupervised oligarchy of masters.

HBR Guide to AI Basics for Managers

Author : Harvard Business Review
Publisher : Harvard Business Press
ISBN 13 : 1647824443
Total Pages : 170 pages
Book Rating : 4.6/5 (478 download)

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Book Synopsis HBR Guide to AI Basics for Managers by : Harvard Business Review

Download or read book HBR Guide to AI Basics for Managers written by Harvard Business Review and published by Harvard Business Press. This book was released on 2023-01-10 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI is ready for business. Are you ready for AI? From financial modeling and product design to performance management and hiring decisions, AI and machine learning are becoming everyday tools for managers at businesses of all sizes. But AI systems come with benefits and downsides—and if you can't make sense of them, you're not going to make the right decisions. Whether you need to get up to speed quickly or need a refresher, or you're working with an AI expert for the first time, the HBR Guide to AI Basics for Managers will give you the information and skills you need to succeed. You'll learn how to: Understand key AI terms and concepts Recognize which of your projects would benefit from AI Work more effectively with your data team Hire the right AI vendors and consultants Deal with ethical risks before they arise Scale AI across your organization Arm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges.

AI 2041

Author : Kai-Fu Lee
Publisher : Crown Currency
ISBN 13 : 0593238311
Total Pages : 497 pages
Book Rating : 4.5/5 (932 download)

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Book Synopsis AI 2041 by : Kai-Fu Lee

Download or read book AI 2041 written by Kai-Fu Lee and published by Crown Currency. This book was released on 2024-03-05 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee. A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning. In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons.

Java Basics Using Chatgpt/Gpt-4

Author : OSWALD. CAMPESATO
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 1501518917
Total Pages : 345 pages
Book Rating : 4.5/5 (15 download)

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Book Synopsis Java Basics Using Chatgpt/Gpt-4 by : OSWALD. CAMPESATO

Download or read book Java Basics Using Chatgpt/Gpt-4 written by OSWALD. CAMPESATO and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-12-28 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed for those new to Java and interested in understanding how ChatGPT/GPT-4 can enhance programming. It offers a unique approach to learning Java, combining traditional hand-written code with cutting-edge ChatGPT-generated examples. The book covers the basics of Java programming and development environments, including understanding recursion, strings, arrays, fundamental data structures, algorithm analysis, queues and stacks, and follows with the role of ChatGPT in generating, explaining, and debugging code. Companion files with source code and figures available for downloading. It's an essential resource for those starting Java programming and for anyone curious about the applications of ChatGPT in coding. FEATURES Combines hand-crafted Java code with ChatGPT-generated examples for a multifaceted learning experience Offers practical Java coding skills, with examples in recursion, data structures, and algorithm analysis Covers the capabilities of ChatGPT for code generation, debugging, and explanation, providing a modern perspective on programming Includes companion files for downloading with source code and figures

Machine Learning Theory and Applications

Author : Xavier Vasques
Publisher : John Wiley & Sons
ISBN 13 : 1394220618
Total Pages : 516 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Machine Learning Theory and Applications by : Xavier Vasques

Download or read book Machine Learning Theory and Applications written by Xavier Vasques and published by John Wiley & Sons. This book was released on 2024-03-06 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enables readers to understand mathematical concepts behind data engineering and machine learning algorithms and apply them using open-source Python libraries Machine Learning Theory and Applications delves into the realm of machine learning and deep learning, exploring their practical applications by comprehending mathematical concepts and implementing them in real-world scenarios using Python and renowned open-source libraries. This comprehensive guide covers a wide range of topics, including data preparation, feature engineering techniques, commonly utilized machine learning algorithms like support vector machines and neural networks, as well as generative AI and foundation models. To facilitate the creation of machine learning pipelines, a dedicated open-source framework named hephAIstos has been developed exclusively for this book. Moreover, the text explores the fascinating domain of quantum machine learning and offers insights on executing machine learning applications across diverse hardware technologies such as CPUs, GPUs, and QPUs. Finally, the book explains how to deploy trained models through containerized applications using Kubernetes and OpenShift, as well as their integration through machine learning operations (MLOps). Additional topics covered in Machine Learning Theory and Applications include: Current use cases of AI, including making predictions, recognizing images and speech, performing medical diagnoses, creating intelligent supply chains, natural language processing, and much more Classical and quantum machine learning algorithms such as quantum-enhanced Support Vector Machines (QSVMs), QSVM multiclass classification, quantum neural networks, and quantum generative adversarial networks (qGANs) Different ways to manipulate data, such as handling missing data, analyzing categorical data, or processing time-related data Feature rescaling, extraction, and selection, and how to put your trained models to life and production through containerized applications Machine Learning Theory and Applications is an essential resource for data scientists, engineers, and IT specialists and architects, as well as students in computer science, mathematics, and bioinformatics. The reader is expected to understand basic Python programming and libraries such as NumPy or Pandas and basic mathematical concepts, especially linear algebra.

Pharmako-AI

Author : K. Allado-McDowell
Publisher :
ISBN 13 : 9781838003906
Total Pages : 0 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Pharmako-AI by : K. Allado-McDowell

Download or read book Pharmako-AI written by K. Allado-McDowell and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book collects essays, stories, and poems ... [the author] wrote with OpenAI's GPT-3 language model, a neural net that generates text sequences"--Page xi.

Responsible AI in the Enterprise

Author : Adnan Masood
Publisher : Packt Publishing Ltd
ISBN 13 : 1803249668
Total Pages : 318 pages
Book Rating : 4.8/5 (32 download)

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Book Synopsis Responsible AI in the Enterprise by : Adnan Masood

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.