Intelligenza Artificiale Un Approccio Moderno

Autore: Stuart J. Russell
Editore: Pearson Italia S.p.a.
ISBN: 9788871922287
Grandezza: 19,92 MB
Formato: PDF, Mobi
Vista: 2201
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Intelligenza Artificiale Un Approccio Moderno

Autore: Stuart J. Russell
ISBN: 9788871925936
Grandezza: 66,65 MB
Formato: PDF, ePub
Vista: 990
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Artificial Intelligence

Autore: Stuart Russell
Editore: Createspace Independent Publishing Platform
ISBN: 9781537600314
Grandezza: 11,88 MB
Formato: PDF, ePub
Vista: 7062
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Artificial Intelligence: A Modern Approach offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.

Deep Learning

Autore: Ian Goodfellow
Editore: MIT Press
ISBN: 0262035618
Grandezza: 13,91 MB
Formato: PDF
Vista: 2713
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An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.

Foundations Of Rational Agency

Autore: M.J. Wooldridge
Editore: Springer
ISBN: 9780792356011
Grandezza: 78,34 MB
Formato: PDF, ePub, Mobi
Vista: 7944
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This volume represents an advanced, comprehensive state-of-the-art survey of the field of rational agency as it stands today. It covers the philosophical foundations of rational agency, logical and decision-theoretic approaches to rational agency, multi-agent aspects of rational agency and a number of approaches to programming rational agents. It will be of interest to researchers in logic, mainstream computer science, the philosophy of rational action and agency, and economics.

Intelligent Help Systems For Unix

Autore: Stephen J. Hegner
Editore: Springer Science & Business Media
ISBN: 9401008744
Grandezza: 19,22 MB
Formato: PDF, ePub, Mobi
Vista: 313
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In this international collection of papers there is a wealth of knowledge on artificial intelligence (AI) and cognitive science (CS) techniques applied to the problem of providing help systems mainly for the UNIX operating system. The research described here involves the representation of technical computer concepts, but also the representation of how users conceptualise such concepts. The collection looks at computational models and systems such as UC, Yucca, and OSCON programmed in languages such as Lisp, Prolog, OPS-5, and C which have been developed to provide UNIX help. These systems range from being menu-based to ones with natural language interfaces, some providing active help, intervening when they believe the user to have misconceptions, and some based on empirical studies of what users actually do while using UNIX. Further papers investigate planning and knowledge representation where the focus is on discovering what the user wants to do, and figuring out a way to do it, as well as representing the knowledge needed to do so. There is a significant focus on natural language dialogue where consultation systems can become active, incorporating user modfelling, natural language generation and plan recognition, modelling metaphors, and users' mistaken beliefs. Much can be learned from seeing how AI and CS techniques can be investigated in depth while being applied to a real test-bed domain such as help on UNIX.

Python Machine Learning

Autore: Sebastian Raschka
Editore: Packt Publishing Ltd
ISBN: 1783555149
Grandezza: 51,21 MB
Formato: PDF
Vista: 9307
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Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

L Intelligenza Artificiale Capire L I A E Le Implicazioni Dell Apprendimento Automatico

Autore: Smart Reads
Editore: Babelcube Inc.
ISBN: 1547506377
Grandezza: 53,99 MB
Formato: PDF
Vista: 4627
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Elon Musk, Stephen Hawking e Bill Gates hanno affermato che l'Intelligenza Artificiale potrebbe costituire una minaccia in futuro a meno che gli umani non imparino a usarla saggiamente. Potrebbe essere vero? Potremo creare un programma di intelligenza artificiale che a breve disporrà di pensiero e sentimenti di IA? Potremo addirittura avere un'IA dall'aspetto umano che si candidi a presidente in futuro? Tutte queste domande e queste riflessioni vengono prese in esame in L'Intelligenza Artificiale: capire l'I.A. e le implicazioni dell'apprendimento automatico. È un libro studiato per offrire una panoramica concisa dei primordi delle macchine intelligenti, del nostro approccio moderno e del suo impatto sulla tecnologia del futuro e sull'esistenza umana.

Semantic Digital Libraries

Autore: Sebastian Ryszard Kruk
Editore: Springer Science & Business Media
ISBN: 3540854347
Grandezza: 21,34 MB
Formato: PDF, Docs
Vista: 5876
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Libraries have always been an inspiration for the standards and technologies developed by semantic web activities. However, except for the Dublin Core specification, semantic web and social networking technologies have not been widely adopted and further developed by major digital library initiatives and projects. Yet semantic technologies offer a new level of flexibility, interoperability, and relationships for digital repositories. Kruk and McDaniel present semantic web-related aspects of current digital library activities, and introduce their functionality; they show examples ranging from general architectural descriptions to detailed usages of specific ontologies, and thus stimulate the awareness of researchers, engineers, and potential users of those technologies. Their presentation is completed by chapters on existing prototype systems such as JeromeDL, BRICKS, and Greenstone, as well as a look into the possible future of semantic digital libraries. This book is aimed at researchers and graduate students in areas like digital libraries, the semantic web, social networks, and information retrieval. This audience will benefit from detailed descriptions of both today’s possibilities and also the shortcomings of applying semantic web technologies to large digital repositories of often unstructured data.

On Care For Our Common Home

Autore: Pope Francis
ISBN: 9781593252830
Grandezza: 46,94 MB
Formato: PDF, ePub, Docs
Vista: 4655
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Addressed not only to Catholics but to"every person living on this planet," Pope Francis' second encyclical is a challenging call for a "bold cultural revolution" in how we think about technological progress and economic growth. The degradation of our environment, he says, is a symptom of deeper problems: rapid change, unsustainable overconsumption, indifference to the poor, and the decay of social values. He offers a variety of solutions, including a change in lifestyles away from "extreme consumerism" and towards a greater sense of social responsibility. For Christians, an "ecological spirituality"-one that is grounded in the convictions of our faith- is not "an optional or a secondary aspect of our Christian experience." Drawing on the rich social teachings of the Church, Laudato Si is a groundbreaking document that will be discussed and studied by both believers and non-believers for years to come. Study guide included for Reflection and Discussion,