A Citizen's Guide to Artificial Intelligence PDF Download
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Author: John Zerilli
Publisher: MIT Press
ISBN: 0262044811
Category : Computers
Languages : en
Pages : 233
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Book Description
A concise but informative overview of AI ethics and policy. Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring home-owners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, voters in liberal democracies? This book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues including transparency, bias, liability, privacy, and regulation.
Author: John Zerilli
Publisher: MIT Press
ISBN: 0262044811
Category : Computers
Languages : en
Pages : 233
Get Book Here
Book Description
A concise but informative overview of AI ethics and policy. Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring home-owners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, voters in liberal democracies? This book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues including transparency, bias, liability, privacy, and regulation.
Author: Shuqiang Wang
Publisher: Frontiers Media SA
ISBN: 2832535070
Category : Science
Languages : en
Pages : 129
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Book Description
Author: Khalid Raza
Publisher: Springer Nature
ISBN: 9819784603
Category :
Languages : en
Pages : 468
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Book Description
Author: Chris Fregly
Publisher: "O'Reilly Media, Inc."
ISBN: 1492079367
Category : Computers
Languages : en
Pages : 524
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Book Description
With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level up your skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more
Author: Chandrakanth Rao Madhavaram
Publisher: JEC PUBLICATION
ISBN: 9361754424
Category : Computers
Languages : en
Pages : 216
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Book Description
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Author: Wojciech Samek
Publisher: Springer Nature
ISBN: 3030289540
Category : Computers
Languages : en
Pages : 435
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Book Description
The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Author: Kendrick Kay
Publisher: Elsevier
ISBN: 0443134812
Category : Science
Languages : en
Pages : 356
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Book Description
Neuroimaging is witnessing a massive increase in the quality and quantity of data being acquired. It is widely recognized that effective interpretation and extraction of information from such data requires quantitative modeling. However, modeling comes in many diverse forms, with different research communities tackling different brain systems, different spatial and temporal scales, and different aspects of brain structure and function. Computational and Network Modeling of Neuroimaging Data provides an authoritative and comprehensive overview of the many diverse modeling approaches that have been fruitfully applied to neuroimaging data. This book gives an accessible foundation to the field of computational and network modeling of neuroimaging data and is suitable for graduate students, academic researchers, and industry practitioners who are interested in adopting or applying model-based approaches in neuroimaging. - Provides an authoritative and comprehensive overview of major modeling approaches to neuroimaging data - Written by experts, the book's chapters use a common structure to introduce, motivate, and describe a specific modeling approach used in neuroimaging - Gives insights into the similarities and differences across different modeling approaches - Analyses details of outstanding research challenges in the field
Author: Joseph Babcock
Publisher: Packt Publishing Ltd
ISBN: 1800208502
Category : Computers
Languages : en
Pages : 489
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Book Description
Fun and exciting projects to learn what artificial minds can create Key FeaturesCode examples are in TensorFlow 2, which make it easy for PyTorch users to follow alongLook inside the most famous deep generative models, from GPT to MuseGANLearn to build and adapt your own models in TensorFlow 2.xExplore exciting, cutting-edge use cases for deep generative AIBook Description Machines are excelling at creative human skills such as painting, writing, and composing music. Could you be more creative than generative AI? In this book, you’ll explore the evolution of generative models, from restricted Boltzmann machines and deep belief networks to VAEs and GANs. You’ll learn how to implement models yourself in TensorFlow and get to grips with the latest research on deep neural networks. There’s been an explosion in potential use cases for generative models. You’ll look at Open AI’s news generator, deepfakes, and training deep learning agents to navigate a simulated environment. Recreate the code that’s under the hood and uncover surprising links between text, image, and music generation. What you will learnExport the code from GitHub into Google Colab to see how everything works for yourselfCompose music using LSTM models, simple GANs, and MuseGANCreate deepfakes using facial landmarks, autoencoders, and pix2pix GANLearn how attention and transformers have changed NLPBuild several text generation pipelines based on LSTMs, BERT, and GPT-2Implement paired and unpaired style transfer with networks like StyleGANDiscover emerging applications of generative AI like folding proteins and creating videos from imagesWho this book is for This is a book for Python programmers who are keen to create and have some fun using generative models. To make the most out of this book, you should have a basic familiarity with math and statistics for machine learning.
Author: Chris Knight
Publisher: Yale University Press
ISBN: 0300221460
Category : Philosophy
Languages : en
Pages : 301
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Book Description
A fresh and fascinating look at the philosophies, politics, and intellectual legacy of one of the twentieth century's most influential and controversial minds Occupying a pivotal position in postwar thought, Noam Chomsky is both the founder of modern linguistics and the world's most prominent political dissident. Chris Knight adopts an anthropologist's perspective on the twin output of this intellectual giant, acclaimed as much for his denunciations of US foreign policy as for his theories about language and mind. Knight explores the social and institutional context of Chomsky's thinking, showing how the tension between military funding and his role as linchpin of the political left pressured him to establish a disconnect between science on the one hand and politics on the other, deepening a split between mind and body characteristic of Western philosophy since the Enlightenment. Provocative, fearless, and engaging, this remarkable study explains the enigma of one of the greatest intellectuals of our time.
Author: Omar Sanseviero
Publisher: "O'Reilly Media, Inc."
ISBN: 1098149211
Category : Computers
Languages : en
Pages : 419
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Book Description
Learn to use generative AI techniques to create novel text, images, audio, and even music with this practical, hands-on book. Readers will understand how state-of-the-art generative models work, how to fine-tune and adapt them to their needs, and how to combine existing building blocks to create new models and creative applications in different domains. This go-to book introduces theoretical concepts followed by guided practical applications, with extensive code samples and easy-to-understand illustrations. You'll learn how to use open source libraries to utilize transformers and diffusion models, conduct code exploration, and study several existing projects to help guide your work. Build and customize models that can generate text and images Explore trade-offs between using a pretrained model and fine-tuning your own model Create and utilize models that can generate, edit, and modify images in any style Customize transformers and diffusion models for multiple creative purposes Train models that can reflect your own unique style
