Artificial Intelligence In Action
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Machine Learning In Action
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Author : Peter Harrington
language : en
Publisher: Manning
Release Date : 2012-04-19
Machine Learning In Action written by Peter Harrington and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-19 with Computers categories.
Summary Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. About the Book A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many. Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification. Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside A no-nonsense introduction Examples showing common ML tasks Everyday data analysis Implementing classic algorithms like Apriori and Adaboos Table of Contents PART 1 CLASSIFICATION Machine learning basics Classifying with k-Nearest Neighbors Splitting datasets one feature at a time: decision trees Classifying with probability theory: naïve Bayes Logistic regression Support vector machines Improving classification with the AdaBoost meta algorithm PART 2 FORECASTING NUMERIC VALUES WITH REGRESSION Predicting numeric values: regression Tree-based regression PART 3 UNSUPERVISED LEARNING Grouping unlabeled items using k-means clustering Association analysis with the Apriori algorithm Efficiently finding frequent itemsets with FP-growth PART 4 ADDITIONAL TOOLS Using principal component analysis to simplify data Simplifying data with the singular value decomposition Big data and MapReduce
The Executive Guide To Artificial Intelligence
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Author : Andrew Burgess
language : en
Publisher: Springer
Release Date : 2017-11-15
The Executive Guide To Artificial Intelligence written by Andrew Burgess and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-15 with Business & Economics categories.
This book takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the core of the book is a framework, developed by the author, which describes in non–technical language the eight core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through natural language processing, to prediction, is explained using real–life examples and how they can be applied in a business environment. It will include interviews with executives who have successfully implemented AI as well as CEOs from AI vendors and consultancies. AI is one of the most talked about technologies in business today. It has the ability to deliver step–change benefits to organisations and enables forward–thinking CEOs to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive that wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in Artificial Intelligence, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the hype that surrounds AI. The knowledge and experience he has gained in advising them, as well as working as a strategic advisor to AI vendors and consultancies, has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies.
Artificial Intelligence In Society
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Author : OECD
language : en
Publisher: OECD Publishing
Release Date : 2019-06-11
Artificial Intelligence In Society written by OECD and has been published by OECD Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-11 with categories.
The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises.
Machine Learning Engineering In Action
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Author : Ben Wilson
language : en
Publisher: Simon and Schuster
Release Date : 2022-05-17
Machine Learning Engineering In Action written by Ben Wilson and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-17 with Computers categories.
Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using standardized prototyping work and statistical validation Choosing the right technologies and tools for your project Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices Ferrying a machine learning project from your data science team to your end users is no easy task. Machine Learning Engineering in Action will help you make it simple. Inside, you'll find fantastic advice from veteran industry expert Ben Wilson, Principal Resident Solutions Architect at Databricks. Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You'll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. About the book Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You'll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the author's extensive experience, every method in this book has been used to solve real-world projects. What's inside Scoping a machine learning project for usage expectations and budget Choosing the right technologies for your design Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices About the reader For data scientists who know machine learning and the basics of object-oriented programming. About the author Ben Wilson is Principal Resident Solutions Architect at Databricks, where he developed the Databricks Labs AutoML project, and is an MLflow committer.
Artificial Intelligence
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Author : John Haugeland
language : en
Publisher: MIT Press
Release Date : 1989-01-06
Artificial Intelligence written by John Haugeland and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989-01-06 with Psychology categories.
"Machines who think—how utterly preposterous," huff beleaguered humanists, defending their dwindling turf. "Artificial Intelligence—it's here and about to surpass our own," crow techno-visionaries, proclaiming dominion. It's so simple and obvious, each side maintains, only a fanatic could disagree. Deciding where the truth lies between these two extremes is the main purpose of John Haugeland's marvelously lucid and witty book on what artificial intelligence is all about. Although presented entirely in non-technical terms, it neither oversimplifies the science nor evades the fundamental philosophical issues. Far from ducking the really hard questions, it takes them on, one by one. Artificial intelligence, Haugeland notes, is based on a very good idea, which might well be right, and just as well might not. That idea, the idea that human thinking and machine computing are "radically the same," provides the central theme for his illuminating and provocative book about this exciting new field. After a brief but revealing digression in intellectual history, Haugeland systematically tackles such basic questions as: What is a computer really? How can a physical object "mean" anything? What are the options for computational organization? and What structures have been proposed and tried as actual scientific models for intelligence? In a concluding chapter he takes up several outstanding problems and puzzles—including intelligence in action, imagery, feelings and personality—and their enigmatic prospects for solution.
Vision Instruction And Action
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Author : David Chapman
language : en
Publisher: Mit Press
Release Date : 1991
Vision Instruction And Action written by David Chapman and has been published by Mit Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Computers categories.
Vision, Instruction, and Action clearly and cleverly describes a sophisticated integrated system called Sonja that takes instruction, can interpret its environment visually, and can play games (in this case the video game, Amazon) on its own. Sonja integrates advances in intermediate visual processing, interactive activity, and natural language pragmatics. In demonstrating that such systems, rare in artificial intelligence, are possible, David Chapman shows how discoveries in visual psychophysics can be incorporated into Al, how complex activity can result from participation rather than plan following, and how physical context can be used to interpret indexical instructions. Sonja is able to play a competent beginner's game of Amazon autonomously and at the same time can also make flexible use of human instructions in knowing how to kill off monsters, pick up and use tools, and find its way in a dungeon maze. It extends the author's previous work in developing a new theory of activity by addressing linguistic issues and providing a better understanding of the architecture underlying activity, incorporating many technical improvements. Sonja also models several pragmatic issues in computational linguistics, focusing on external reference and including linguistic repair processing, and the use of temporal and spatial expressions. It connects language use with more detailed and realistic theories of vision and activity. In the field of vision research, Sonja provides an implementation of a unified visual architecture, demonstrating that this architecture can support a serious theory of activity. It demonstrates the first instance that various visual mechanisms previously proposed on psychophysical, neurophysiological, and speculative computational grounds can be made useful by connecting them with a natural task domain. David Chapman is a Computer Scientist with Teleos Research in Palo Alto.
Fundamentals Of Robotics
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Author : Min Xie
language : en
Publisher: World Scientific
Release Date : 2003
Fundamentals Of Robotics written by Min Xie and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Technology & Engineering categories.
Tomorrow's robots, which includes the humanoid robot, can perform task like tutoring children, working as tour guides, driving humans to and from work, do the family shopping etc. Tomorrow's robots will enhance lives in ways we never dreamed possible. No time to attend the decisive meeting on Asian strategy? Let your robot go for you and make the decisions. Not feeling well enough to go to the clinic? Let Dr Robot come to you, make a diagnosis, and get you the necessary medicine for treatment. No time to coach the soccer team this week? Let the robot do it for you. Tomorrow's robots will be the most exciting and revolutionary things to happen to the world since the invention of the automobile. It will change the way we work, play, think, and live. Because of this, nowadays robotics is one of the most dynamic fields of scientific research. These days, robotics is offered in almost every university in the world. Most mechanical engineering departments offer a similar course at both the undergraduate and graduate levels. And increasingly, many computer and electrical engineering departments are also offering it. This book will guide you, the curious beginner, from yesterday to tomorrow. The book will cover practical knowledge in understanding, developing, and using robots as versatile equipment to automate a variety of industrial processes or tasks. But, the book will also discuss the possibilities we can look forward to when we are capable of creating a vision-guided, learning machine. Readership: Upper-level undergraduates, graduates and researchers in robotics &automated systems, artificial intelligence, machine perception and computer vision.
Artificial Intelligence In Action
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Author : Charles Platt
language : en
Publisher: Trillium Press
Release Date : 1985-05-01
Artificial Intelligence In Action written by Charles Platt and has been published by Trillium Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985-05-01 with categories.
Action Programming Languages
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Author : Michael Thielscher
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2008
Action Programming Languages written by Michael Thielscher and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
Artificial systems that think and behave intelligently are one of the most exciting and challenging goals of Artificial Intelligence. Action Programming is the art and science of devising high-level control strategies for autonomous systems which employ a mental model of their environment and which reason about their actions as a means to achieve their goals. Applications of this programming paradigm include autonomous software agents, mobile robots with high-level reasoning capabilities, and General Game Playing. These lecture notes give an in-depth introduction to the current state-of-the-art in action programming. The main topics are knowledge representation for actions, procedural action programming, planning, agent logic programs, and reactive, behavior-based agents. The only prerequisite for understanding the material in these lecture notes is some general programming experience and basic knowledge of classical first-order logic.
Artificial Intelligence Methods And Applications
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Author : Aristidis Likas
language : en
Publisher: Springer
Release Date : 2014-04-18
Artificial Intelligence Methods And Applications written by Aristidis Likas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-18 with Computers categories.
This book constitutes the proceedings of the 8th Hellenic Conference on Artificial Intelligence, SETN 2014, held in Ioannina, Greece, in May 2014. There are 34 regular papers out of 60 submissions, in addition 5 submissions were accepted as short papers and 15 papers were accepted for four special sessions. They deal with emergent topics of artificial intelligence and come from the SETN main conference as well as from the following special sessions on action languages: theory and practice; computational intelligence techniques for bio signal Analysis and evaluation; game artificial intelligence; multimodal recommendation systems and their applications to tourism.