Building Intelligent Systems
Building Intelligent Systems

Author: Geoff Hulten

Publisher: Apress

Published: 2018-03-06

Total Pages: 346

ISBN-13: 1484234324

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Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success. This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems. Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You’ll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for success Design an intelligent user experience: Produce data to help make the Intelligent System better over time Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice Create intelligence: Use different approaches, including machine learning Orchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want Who This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems

ARTIFICIAL INTELLIGENCE
ARTIFICIAL INTELLIGENCE

Author: PARAG KULKARNI

Publisher: PHI Learning Pvt. Ltd.

Published: 2015-02-26

Total Pages: 529

ISBN-13: 8120350464

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There has been a movement over the years to make machines intelligent. With the advent of modern technology, AI has become the core part of day-to-day life. But it is accentuated to have a book that keeps abreast of all the state-of-the-art concepts (pertaining to AI) in simplified, explicit and elegant way, expounding on ample examples so that the beginners are able to comprehend the subject with ease. The book on Artificial Intelligence, dexterously divided into 21 chapters, fully satisfies all these pressing needs. It is intended to put each and every concept related to intelligent system in front of the readers in the most simplified way so that while understanding the basic concepts, they will develop thought process that can contribute to the building of advanced intelligent systems. Various cardinal landmarks pertaining to the subject such as problem solving, search techniques, intelligent agents, constraint satisfaction problems, knowledge representation, planning, machine learning, natural language processing, pattern recognition, game playing, hybrid and fuzzy systems, neural network-based learning and future work and trends in AI are now under the single umbrella of this book, thereby showing a nice blend of theoretical and practical aspects. With all the latest information incorporated and several pedagogical attributes included, this textbook is an invaluable learning tool for the undergraduate and postgraduate students of computer science and engineering, and information technology. KEY FEATURES • Highlights a clear and concise presentation through adequate study material • Follows a systematic approach to explicate fundamentals as well as recent advances in the area • Presents ample relevant problems in the form of multiple choice questions, concept review questions, critical thinking exercise and project work • Incorporates various case studies for major topics as well as numerous industrial examples

Intelligent Building Systems
Intelligent Building Systems

Author: Albert Ting-pat So

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 191

ISBN-13: 146155019X

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Intelligent building is the future of our building industry; all commercial, residential, industrial and institutional buildings will be designed towards the goal of `intelligent buildings'. The most important aspect of an intelligent building is the building systems, such as electrical services, heating, ventilation and air-conditioning systems, vertical transportation systems, and life safety systems, which must operate intelligently and efficiently to enhance the activities of the occupants. Intelligent Building Systems explains what already exists in a modern intelligent building and describes what is currently being developed by researchers to improve human comfort, working efficiency and energy performance for buildings in the 21st century. Intelligent Building Systems is divided into three parts. The first part gives a quick review of the structure, terminology, layout and operating principles of most standard modern building systems. The second part introduces the background material necessary to understand intelligent building systems, including information on electronics technology, fundamental mathematics, and techniques in artificial intelligence and signal processing. These first two parts are the foundation for the final part, which consists of research works carried out by the authors and other researchers in the application of artificial intelligence to building systems. The technologies presented will encourage readers to envision new and innovative ideas on possible future applications. Intelligent Building Systems is relevant to practitioners and researchers in the area of architectural science and engineering, electrical and mechanical services and intelligent buildings. It may also be used as a text for advanced courses on the topic.

Building Intelligent Systems: Utilizing Computer Vision, Data Mining, and Machine Learning
Building Intelligent Systems: Utilizing Computer Vision, Data Mining, and Machine Learning

Author: Phil Tian

Publisher:

Published: 2013-05-21

Total Pages: 460

ISBN-13: 9781934053522

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Consumers are now demanding and expecting more from technology. Building intelligence into our devices is a promising way to satisfy this demand by providing more personalized experiences. In Building Intelligent Systems the authors investigate how computer vision, machine learning, and data mining can be used together to build smarter devices and systems. Additionally, they explore some of the practical considerations of using artificial intelligence in the real world, tackling issues that are often overlooked in academic circles, such as performance optimization, benchmarking, robustness, and privacy.

Building Intelligent Interactive Tutors
Building Intelligent Interactive Tutors

Author: Beverly Park Woolf

Publisher: Morgan Kaufmann

Published: 2010-07-28

Total Pages: 480

ISBN-13: 0080920047

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Building Intelligent Interactive Tutors discusses educational systems that assess a student's knowledge and are adaptive to a student's learning needs. The impact of computers has not been generally felt in education due to lack of hardware, teacher training, and sophisticated software. and because current instructional software is neither truly responsive to student needs nor flexible enough to emulate teaching. Dr. Woolf taps into 20 years of research on intelligent tutors to bring designers and developers a broad range of issues and methods that produce the best intelligent learning environments possible, whether for classroom or life-long learning. The book describes multidisciplinary approaches to using computers for teaching, reports on research, development, and real-world experiences, and discusses intelligent tutors, web-based learning systems, adaptive learning systems, intelligent agents and intelligent multimedia. It is recommended for professionals, graduate students, and others in computer science and educational technology who are developing online tutoring systems to support e-learning, and who want to build intelligence into the system. Combines both theory and practice to offer most in-depth and up-to-date treatment of intelligent tutoring systems available Presents powerful drivers of virtual teaching systems, including cognitive science, artificial intelligence, and the Internet Features algorithmic material that enables programmers and researchers to design building components and intelligent systems

Intelligent Systems for Engineers and Scientists
Intelligent Systems for Engineers and Scientists

Author: Adrian A. Hopgood

Publisher: CRC Press

Published: 2012-02-02

Total Pages: 455

ISBN-13: 1466516178

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The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself. The first part of the book describes key techniques of artificial intelligence—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance. Check out the significantly expanded set of free web-based resources that support the book at: http://www.adrianhopgood.com/aitoolkit/

Naturally Intelligent Systems
Naturally Intelligent Systems

Author: Maureen Caudill

Publisher: MIT Press

Published: 1990

Total Pages: 324

ISBN-13: 9780262531139

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Naturally Intelligent Systems offers a comprehensive introduction to neural networks.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Author: Aurélien Géron

Publisher: "O'Reilly Media, Inc."

Published: 2019-09-05

Total Pages: 851

ISBN-13: 149203259X

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Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets

Building Machine Learning Systems with Python
Building Machine Learning Systems with Python

Author: Willi Richert

Publisher: Packt Publishing Ltd

Published: 2013-01-01

Total Pages: 431

ISBN-13: 1782161414

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This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into their projects, or who want to pro.

Building Intelligent Agents
Building Intelligent Agents

Author: Gheorghe Tecuci

Publisher: Morgan Kaufmann

Published: 1998-06-23

Total Pages: 356

ISBN-13: 9780126851250

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Building Intelligent Agents is unique in its comprehensive coverage of the subject. The first part of the book presents an original theory for building intelligent agents and a methodology and tool that implement the theory. The second part of the book presents complex and detailed case studies of building different types of agents: an educational assessment agent, a statistical analysis assessment and support agent, an engineering design assistant, and a virtual military commander. Also featured in this book is Disciple, a toolkit for building interactive agents which function in much the same way as a human apprentice. Disciple-based agents can reason both with incomplete information, but also with information that is potentially incorrect. This approach, in which the agent learns its behavior from its teacher, integrates many machine learning and knowledge acquisition techniques, taking advantage of their complementary strengths to compensate for each others weakness. As a consequence, it significantly reduces (or even eliminates) the involvement of a knowledge engineer in the process of building an intelligent agent.