This book offers a highly accessible introduction to Natural Language Processing, the field that underpins a variety of language technologies, ranging from predictive text and email filtering to automatic summarization and translation. With Natural Language Processing with Python, you'll learn how to write Python programs to work with large collections of unstructured text. You'll access richly-annotated datasets using a comprehensive range of linguistic data structures. And you'll understand the main algorithms for analyzing the content and structure of written communication.
Packed with examples and exercises, Natural Language Processing with Python will help you:
* Extract information from unstructured text, to guess the topic or identify "named entities"
* Analyze linguistic structure in text, including parsing and semantic analysis
* Access popular linguistic databases, including WordNet and treebanks
* Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence
Perfect for individual study, or as a classroom and workshop textbook, this book will help you gain practical skills in Natural Language Processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library.
If you're interested in developing Web applications, analyzing multilingual news sources, documenting endangered languages, or if you are simply curious to have a programmer's perspective on how human language works, you will find Natural Language Processing with Python both fascinating and immensely useful.

Computers and Thought showcases the work of the scientists who not only defined the field of Artificial Intelligence, but who are responsible for having developed it into what it is today. Originally published in 1963, this collection includes twenty classic papers by such pioneers as A. M. Turing and Marvin Minsky who were behind the pivotal advances in artificially simulating human thought processes with computers.Among the now hard-to-find articles are reports of computer programs that play chess and checkers, prove theorems in logic and geometry, solve problems in calculus, balance assembly lines, recognize visual temporal patterns, and communicate in natural language. The reports of simulation of cognitive processes include computer models of human behavior in logic problems, deciding on common stock portfolios, and carrying out social interaction. Models of verbal learning behavior, predictive behavior in two-choice experiments, and concept formation are also included.Articles by : Paul Armer. Carol Chomsky. Geoffrey P. E. Clarkson. Edward A. Feigenbaum. Julian Feldman. H. Gelernter. Bert F. Green, Jr. John T. Gullahorn. Jeanne E. Gullahorn. J. R. Hansen. Carl I. Hovland. Earl B. Hunt. Kenneth Laughery. Robert K. Lindsay. D. W. Loveland. Marvin Minsky. Ulric Neisser. Allen Newell. A. L. Samuel. Oliver G. Selfridge. J. C. Shaw. Herbert A. Simon. James R. Slagle. Fred M. Tonge. A. M. Turing. Leonard Uhr. Charles Vossler. Alice K. Wolf.

Few books on software project management have been as influential and timeless asThe Mythical Man-Month. With a blend of software engineering facts and thought-provoking opinions, Fred Brooks offers insight for anyone managing complex projects. These essays draw from his experience as project manager for the IBM System/360 computer family and then for OS/360, its massive software system. Now, 20 years after the initial publication of his book, Brooks has revisited his original ideas and added new thoughts and advice, both for readers already familiar with his work and for readers discovering it for the first time. The added chapters contain (1) a crisp condensation of all the propositions asserted in the original book, including Brooks' central argument in The Mythical Man-Month: that large programming projects suffer management problems different from small ones due to the division of labor; that the conceptual integrity of the product is therefore critical; and that it is difficult but possible to achieve this unity; (2) Brooks' view of these propositions a generation later; (3) a reprint of his classic 1986 paper "No Silver Bullet"; and (4) today's thoughts on the 1986 assertion, "There will be no silver bullet within ten years."

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Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making.
In Data Driven , Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals:
The special properties that make data such a powerful asset
The hidden costs of flawed, outdated, or otherwise poor-quality data
How to improve data quality for competitive advantage
Strategies for exploiting your data to make better business decisions
The many ways to bring data to market
Ideas for dealing with political struggles over data and concerns about privacy rights
Your company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that.

For this inexpensive paperback edition of a groundbreaking classic, the author has extensively rearranged, rewritten and enlarged the material. Book is unique in its emphasis on the frequency approach and its use in the solution of problems. Contents include: Fundamentals and Algorithms; Polynomial Approximation -- Classical Theory; Fourier Approximation -- Modern Therory; Exponential Approximation.

Highly effective thinking is an art that engineers and scientists can be taught to develop. By presenting actual experiences and analyzing them as they are described, the author conveys the developmental thought processes employed and shows a style of thinking that leads to successful results is something that can be learned. Along with spectacular successes, the author also conveys how failures contributed to shaping the thought processes.
Provides the reader with a style of thinking that will enhance a person's ability to function as a problem-solver of complex technical issues. Consists of a collection of stories about the author's participation in significant discoveries, relating how those discoveries came about and, most importantly, provides analysis about the thought processes and reasoning that took place as the author and his associates progressed through engineering problems.

"Introduction to Computing Systems: From bits & gates to C & beyond", now in its second edition, is designed to give students a better understanding of computing early in their college careers in order to give them a stronger foundation for later courses. The book is in two parts: the underlying structure of a computer, and programming in a high level language and programming methodology. To understand the computer, the authors introduce the LC-3 and provide the LC-3 Simulator to give students hands-on access for testing what they learn. To develop their understanding of programming and programming methodology, they use the C programming language.The book takes a "motivated" bottom-up approach, where the students first get exposed to the big picture and then start at the bottom and build their knowledge bottom-up. Within each smaller unit, the same motivated bottom-up approach is followed. Every step of the way, students learn new things, building on what they already know. The authors feel that this approach encourages deeper understanding and downplays the need for memorizing. Students develop a greater breadth of understanding, since they see how the various parts of the computer fit together.

This book describes ggplot2, a new data visualization package for R that uses the insights from Leland Wilkison''s Grammar of Graphics to create a powerful and flexible system for creating data graphics. With ggplot2, it''s easy to:
* produce handsome, publication-quality plots, with automatic legends created from the plot specification
* superpose multiple layers (points, lines, maps, tiles, box plots to name a few) from different data sources, with automatically adjusted common scales
* add customisable smoothers that use the powerful modelling capabilities of R, such as loess, linear models, generalised additive models and robust regression
* save any ggplot2 plot (or part thereof) for later modification or reuse
* create custom themes that capture in-house or journal style requirements, and that can easily be applied to multiple plots
* approach your graph from a visual perspective, thinking about how each component of the data is represented on the final plot.
This book will be useful to everyone who has struggled with displaying their data in an informative and attractive way. You will need some basic knowledge of R (i.e. you should be able to get your data into R), but ggplot2 is a mini-language specifically tailored for producing graphics, and you''ll learn everything you need in the book. After reading this book you''ll be able to produce graphics customized precisely for your problems, and you''ll find it easy to get graphics out of your head and on to the screen or page.

Classical computationalism -- -the view that mental states are computational states -- -has come under attack in recent years. Critics claim that in defining computation solely in abstract, syntactic terms, computationalism neglects the real-time, embodied, real-world constraints with which cognitive systems must cope. Instead of abandoning computationalism altogether, however, some researchers are reconsidering it, recognizing that real-world computers, like minds, must deal with issues of embodiment, interaction, physical implementation, and semantics.This book lays the foundation for a successor notion of computationalism. It covers a broad intellectual range, discussing historic developments of the notions of computation and mechanism in the computationalist model, the role of Turing machines and computational practice in artificial intelligence research, different views of computation and their role in the computational theory of mind, the nature of intentionality, and the origin of language.

The national bestseller by the "ultimate thinking machine" ( Forbes ) whose predictions for the future are startling, provocative--and closer to fruition than you think.
Ray Kurzweil is the inventor of the most innovative and compelling technology of our era, an international authority on artificial intelligence, and one of our greatest living visionaries. Now he offers a framework for envisioning the twenty-first century--an age in which the marriage of human sensitivity and artificial intelligence fundamentally alters and improves the way we live. Kurzweil's prophetic blueprint for the future takes us through the advances that inexorably result in computers exceeding the memory capacity and computational ability of the human brain by the year 2020 (with human-level capabilities not far behind); in relationships with automated personalities who will be our teachers, companions, and lovers; and in information fed straight into our brains along direct neural pathways. Optimistic and challenging, thought-provoking and engaging, The Age of Spiritual Machines is the ultimate guide on our road into the next century.
" The Age of Spiritual Machines will blow your mind. . . . Kurzweil lays out a scenario that might seem like science fiction if it weren't coming from a proven entrepreneur."-- San Francisco Chronicle
The Age of Spiritual Machines appeared on national bestseller lists, including the Boston Globe and the San Francisco Chronicle
Kurzweil's first book, The Age of Intelligent Machines , won the Association of American Publishers Award for the Most Outstanding Computer Science Book of 1990

Review
"A must-read resource for anyone who is serious about embracing the opportunity of big data."
-- Craig Vaughan
Global Vice President at SAP
"This book goes beyond data analytics 101. It's the essential guide for those of us (all of us?) whose businesses are built on the ubiquity of data opportunities and the new mandate for data-driven decision-making."
--Tom Phillips
CEO of Media6Degrees and Former Head of Google Search and Analytics
"Data is the foundation of new waves of productivity growth, innovation, and richer customer insight. Only recently viewed broadly as a source of competitive advantage, dealing well with data is rapidly becoming table stakes to stay in the game. The authors' deep applied experience makes this a must read--a window into your competitor's strategy."
-- Alan Murray
Serial Entrepreneur; Partner at Coriolis Ventures
"This timely book says out loud what has finally become apparent: in the modern world, Data is Business, and you can no longer think business without thinking data. Read this book and you will understand the Science behind thinking data."
-- Ron Bekkerman
Chief Data Officer at Carmel Ventures
"A great book for business managers who lead or interact with data scientists, who wish to better understand the principles and algorithms available without the technical details of single-disciplinary books."
-- Ronny Kohavi
Partner Architect at Microsoft Online Services Division
About the Author
Foster Provost is Professor and NEC Faculty Fellow at the NYU Stern School of Business where he teaches in the MBA, Business Analytics, and Data Science programs. His award-winning research is read and cited broadly. Prof. Provost has co-founded several successful companies focusing on data science for marketing.
Tom Fawcett holds a Ph.D. in machine learning and has worked in industry R&D for more than two decades for companies such as GTE Laboratories, NYNEX/Verizon Labs, and HP Labs. His published work has become standard reading in data science.

'What is a self, and how can a self come out of inaminate matter?' This is the riddle that drove Hofstadter to write this extraordinary book. Linking together the music of J.S. Bach, the graphic art of Escher and the mathematical theorems of Godel, as well as ideas drawn from logic, biology, psychology, physics and linguistics, Douglas Hofstadter illuminates one of the greatest mysteries of modern science: the nature of human thought processes. 'Every few decades an unknown author brings outa book of such depth, clarity, range, wit, beauty and originality that it is recognized at once as a major literary event. This is such a work' - Martin Gardner

For over three decades, Ray Kurzweil has been one of the most respected and provocative advocates of the role of technology in our future. In his classic The Age of Spiritual Machines , he argued that computers would soon rival the full range of human intelligence at its best. Now he examines the next step in this inexorable evolutionary process: the union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.

First published in 1958, John von Neumann's classic work "The Computer and the Brain" explored the analogies between computing machines and the living human brain. Von Neumann showed that the brain operates both digitally and analogically, but also has its own unique statistical language. And more than fifty years after its inception the "von Neumann architecture" - an organizational framework for computer design - still lies at the heart of today's machines. In his foreword to this new edition, Ray Kurzweil, a futurist famous for his own musings on the relationship between technology and consciousness, places von Neumann's work in a historical context and shows how it remains relevant today.

In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes, the book can be used as a self-contained introduction to Bayesian analysis. In addition, much of the decision-theoretic portion of the text was updated, including new sections covering such modern topics as minimax multivariate (Stein) estimation.

The practice of enterprise application development has benefited from the emergence of many new enabling technologies. Multi-tiered object-oriented platforms, such as Java and .NET, have become commonplace. These new tools and technologies are capable of building powerful applications, but they are not easily implemented. Common failures in enterprise applications often occur because their developers do not understand the architectural lessons that experienced object developers have learned. Patterns of Enterprise Application Architecture is written in direct response to the stiff challenges that face enterprise application developers. The author, noted object-oriented designer Martin Fowler, noticed that despite changes in technology--from Smalltalk to CORBA to Java to .NET--the same basic design ideas can be adapted and applied to solve common problems. With the help of an expert group of contributors, Martin distills over forty recurring solutions into patterns. The result is an indispensable handbook of solutions that are applicable to any enterprise application platform. This book is actually two books in one. The first section is a short tutorial on developing enterprise applications, which you can read from start to finish to understand the scope of the book's lessons. The next section, the bulk of the book, is a detailed reference to the patterns themselves. Each pattern provides usage and implementation information, as well as detailed code examples in Java or C#. The entire book is also richly illustrated with UML diagrams to further explain the concepts. Armed with this book, you will have the knowledge necessary to make important architectural decisions about building an enterprise application and the proven patterns for use when building them. The topics covered include * Dividing an enterprise application into layers * The major approaches to organizing business logic * An in-depth treatment of mapping between objects and relational databases * Using Model-View-Controller to organize a Web presentation * Handling concurrency for data that spans multiple transactions * Designing distributed object interfaces

Douglas Hofstadter's long-awaited return to the themes of Gödel, Escher, Bach--an original and controversial view of the nature of consciousness and identity.
Can thought arise out of matter? Can self, a soul, a consciousness, an "I" arise out of mere matter? If it cannot, then how can you or I be here?
I Am a Strange Loop argues that the key to understanding selves and consciousness is the "strange loop"--a special kind of abstract feedback loop inhabiting our brains. The most central and complex symbol in your brain or mine is the one called "I." The "I" is the nexus in our brain, one of many symbols seeming to have free will and to have gained the paradoxical ability to push particles around, rather than the reverse.
How can a mysterious abstraction be real--or is our "I" merely a convenient fiction? Does an "I" exert genuine power over the particles in our brain, or is it helplessly pushed around by the laws of physics?
These are the mysteries tackled in I Am a Strange Loop, Douglas R. Hofstadter's first book-length journey into philosophy since Gödel, Escher, Bach. Compulsively readable and endlessly thought-provoking, this is the book Hofstadter's many readers have been waiting for.