Intelligenza Artificiale

Autore: LeonardoEdizioni
ISBN: 882832466X
Grandezza: 28,83 MB
Formato: PDF, Mobi
Vista: 3981
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Questo libro intende trattare gli aspetti riguardanti l'Intelligenza artificiale sia dal punto di vista teorico che dal punto di vista pratico. Il libro non approfondisce i singoli argomenti lasciando ad altri testi gli opportuni approfondimenti, ma punta a realizzare una panoramica della materia. Essendo la materia estremamente estesa il libro tratta solo i temi ritenuti classici dell'intelligenza artificiale quindi prevalentemente l'apprendimento automatico tralasciando molte tecniche e paradigmi legati alla materia.

Artificial Intelligence

Autore: Stuart Russell
Editore: Createspace Independent Publishing Platform
ISBN: 9781537600314
Grandezza: 46,39 MB
Formato: PDF
Vista: 3688
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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.

Artificial Intelligence With Python

Autore: Prateek Joshi
Editore: Packt Publishing Ltd
ISBN: 1786469677
Grandezza: 71,43 MB
Formato: PDF, ePub, Docs
Vista: 4325
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Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.

Machine Learning

Autore: Peter Flach
Editore: Cambridge University Press
ISBN: 1107096391
Grandezza: 28,12 MB
Formato: PDF, Docs
Vista: 1977
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Covering all the main approaches in state-of-the-art machine learning research, this will set a new standard as an introductory textbook.

Fundamentals Of Deep Learning

Autore: Nikhil Buduma
Editore: "O'Reilly Media, Inc."
ISBN: 1491925566
Grandezza: 17,42 MB
Formato: PDF, Docs
Vista: 1884
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With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning

Deep Learning

Autore: Ian Goodfellow
Editore: MIT Press
ISBN: 0262337371
Grandezza: 11,28 MB
Formato: PDF, ePub, Mobi
Vista: 8890
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"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -- Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Reti Neurali E Neurofuzzy

Autore: Marco Buttolo
ISBN: 9788897599586
Grandezza: 64,71 MB
Formato: PDF, ePub
Vista: 5516
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Intelligent Help Systems For Unix

Autore: Stephen J. Hegner
Editore: Springer Science & Business Media
ISBN: 9401008744
Grandezza: 61,47 MB
Formato: PDF
Vista: 2584
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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.

Paradigms Of Artificial Intelligence Programming

Autore: Peter Norvig
Editore: Morgan Kaufmann
ISBN: 0080571158
Grandezza: 58,59 MB
Formato: PDF, Kindle
Vista: 207
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Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.

The Tao Of Physics

Autore: Fritjof Capra
Editore: Shambhala Publications
ISBN: 1590308352
Grandezza: 23,20 MB
Formato: PDF, Kindle
Vista: 9753
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Studies similarities between the concept of a harmonious universe that emerges from the theories of modern physics and the vision of a continuously interactive world conceived by Eastern mystics.