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|Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit
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Author: Steven Bird
Brand: Brand: O'Reilly Media
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that 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, either 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
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, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python
both fascinating and immensely useful.
- Used Book in Good Condition
- Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
- Web Scraping with Python: Collecting Data from the Modern Web
- Text Analytics with Python: A Practical Real-World Approach to Gaining Actionable Insights from your Data
- Introduction to Machine Learning with Python: A Guide for Data Scientists
- Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More
- Foundations of Statistical Natural Language Processing
- Text Mining with R: A Tidy Approach
- Taming Text: How to Find, Organize, and Manipulate It
- Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
- Speech and Language Processing, 2nd Edition
|Text Mining with R: A Tidy Approach
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Author: Julia Silge
Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.
The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You’ll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media.
- Learn how to apply the tidy text format to NLP
- Use sentiment analysis to mine the emotional content of text
- Identify a document’s most important terms with frequency measurements
- Explore relationships and connections between words with the ggraph and widyr packages
- Convert back and forth between R’s tidy and non-tidy text formats
- Use topic modeling to classify document collections into natural groups
- Examine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages
|How to Create a Mind: The Secret of Human Thought Revealed
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Author: Ray Kurzweil
Brand: Brand: Penguin Books
The bold futurist and bestselling author explores the limitless potential of reverse-engineering the human brain
Ray Kurzweil is arguably today’s most influential—and often controversial—futurist. In How to Create a Mind, Kurzweil presents a provocative exploration of the most important project in human-machine civilization—reverse engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines.
Kurzweil discusses how the brain functions, how the mind emerges from the brain, and the implications of vastly increasing the powers of our intelligence in addressing the world’s problems. He thoughtfully examines emotional and moral intelligence and the origins of consciousness and envisions the radical possibilities of our merging with the intelligent technology we are creating.
Certain to be one of the most widely discussed and debated science books of the year, How to Create a Mind is sure to take its place alongside Kurzweil’s previous classics which include Fantastic Voyage: Live Long Enough to Live Forever and The Age of Spiritual Machines.
From the Hardcover edition.
- Used Book in Good Condition
|The Sentient Machine: The Coming Age of Artificial Intelligence
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Author: Amir Husain
The future is now. Acclaimed technologist and inventor Amir Husain explains how we can live amidst the coming age of sentient machines and artificial intelligence—and not only survive, but thrive.
Artificial “machine” intelligence is playing an ever-greater role in our society. We are already using cruise control in our cars, automatic checkout at the drugstore, and are unable to live without our smartphones. The discussion around AI is polarized; people think either machines will solve all problems for everyone, or they will lead us down a dark, dystopian path into total human irrelevance. Regardless of what you believe, the idea that we might bring forth intelligent creation can be intrinsically frightening. But what if our greatest role as humans so far is that of creators?
Amir Husain, a brilliant inventor and computer scientist, argues that we are on the cusp of writing our next, and greatest, creation myth. It is the dawn of a new form of intellectual diversity, one that we need to embrace in order to advance the state of the art in many critical fields, including security, resource management, finance, and energy. “In The Sentient Machine, Husain prepares us for a brighter future; not with hyperbole about right and wrong, but with serious arguments about risk and potential” (Dr. Greg Hyslop, Chief Technology Officer, The Boeing Company). He addresses broad existential questions surrounding the coming of AI: Why are we valuable? What can we create in this world? How are we intelligent? What constitutes progress for us? And how might we fail to progress? Husain boils down complex computer science and AI concepts into clear, plainspoken language and draws from a wide variety of cultural and historical references to illustrate his points. Ultimately, Husain challenges many of our societal norms and upends assumptions we hold about “the good life.”
|Machine Learning For Absolute Beginners: A Plain English Introduction
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Author: Oliver Theobald
Please note that this book is not a sequel to the First Edition, but rather a restructured and revamped version of the First Edition.
Ready to crank up a virtual server and smash through petabytes of data? Want to add 'Machine Learning' to your LinkedIn profile?
Well, hold on there...
Before you embark on your epic journey into the world of machine learning, there is some theory and statistical principles to march through first. But rather than spend $30-$50 USD on a dense long textbook, you may want to read this book first. As a clear and concise alternative to a textbook, this book provides a practical and high-level introduction to the practical components and statistical concepts found in machine learning. Machine Learning for Absolute Beginners Second Edition has been written and designed for absolute beginners. This means plain-English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home. This major new edition features many topics not covered in the First Edition, including Cross Validation, Data Scrubbing and Ensemble Modeling. Please note that this book is not a sequel to the First Edition, but rather a restructured and revamped version of the First Edition. Readers of the First Edition should not feel compelled to purchase this Second Edition. Disclaimer: If you have passed the 'beginner' stage in your study of machine learning and are ready to tackle coding and deep learning, you would be well served with a long-format textbook. If, however, you are yet to reach that Lion King moment—as a fully grown Simba looking over the Pride Lands of Africa—then this is the book to gently hoist you up and offer you a clear lay of the land.
In this step-by-step guide you will learn: - How to download free datasets - What tools and machine learning libraries you need - Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data - Preparing data for analysis, including k-fold Validation - Regression analysis to create trend lines - Clustering, including k-means and k-nearest Neighbors - The basics of Neural Networks - Bias/Variance to improve your machine learning model - Decision Trees to decode classification - How to build your first Machine Learning Model to predict house values using Python Frequently Asked Questions Q: Do I need programming experience to complete this book? A: This book is designed for absolute beginners, so no programming experience is required. However, two of the later chapters introduce Python to demonstrate an actual machine learning model, so you will see programming language used in this book. Q: I have already purchased the First Edition of this book, should I purchase this Second Edition? A: As majority of the topics from the First Edition are covered in the Second Edition, you may be better served reading a more advanced title on machine learning. Q: Can I get access to the Kindle version of this book? A: Yes. Under Amazon’s Matchbook program, the purchaser of this book can add the Kindle version of this title (valued at $3.99 USD) to their Amazon Kindle library at no cost. Q: Does this book include everything I need to become a machine learning expert? A: This book is designed for readers taking their first steps in machine learning and further learning will be required beyond this book to master machine learning.
|Concrete Mathematics: A Foundation for Computer Science (2nd Edition)
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Author: Ronald L. Graham
Brand: Ronald Graham
This book introduces the mathematics that supports advanced computer programming and the analysis of algorithms. The primary aim of its well-known authors is to provide a solid and relevant base of mathematical skills - the skills needed to solve complex problems, to evaluate horrendous sums, and to discover subtle patterns in data. It is an indispensable text and reference not only for computer scientists - the authors themselves rely heavily on it! - but for serious users of mathematics in virtually every discipline.
Concrete Mathematics is a blending of CONtinuous and disCRETE mathematics. "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems." The subject matter is primarily an expansion of the Mathematical Preliminaries section in Knuth's classic Art of Computer Programming, but the style of presentation is more leisurely, and individual topics are covered more deeply. Several new topics have been added, and the most significant ideas have been traced to their historical roots. The book includes more than 500 exercises, divided into six categories. Complete answers are provided for all exercises, except research problems, making the book particularly valuable for self-study.
Major topics include:
- Integer functions
- Elementary number theory
- Binomial coefficients
- Generating functions
- Discrete probability
- Asymptotic methods
This second edition includes important new material about mechanical summation. In response to the widespread use of the first edition as a reference book, the bibliography and index have also been expanded, and additional nontrivial improvements can be found on almost every page. Readers will appreciate the informal style of Concrete Mathematics. Particularly enjoyable are the marginal graffiti contributed by students who have taken courses based on this material. The authors want to convey not only the importance of the techniques presented, but some of the fun in learning and using them.
- Concrete Mathematics A Foundation for Computer Science
|What To Do When Machines Do Everything: How to Get Ahead in a World of AI, Algorithms, Bots, and Big Data
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Author: Malcolm Frank
“Refreshingly thought-provoking…” – The Financial Times
The essential playbook for the future of your business
What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Illustrated with real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created.
Written by a team of business and technology expert practitioners—who also authored Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business—this book provides a clear path to the future of your work.
The first part of the book examines the once in a generation upheaval most every organization will soon face as systems of intelligence go mainstream. The authors argue that contrary to the doom and gloom that surrounds much of IT and business at the moment, we are in fact on the cusp of the biggest wave of opportunity creation since the Industrial Revolution. Next, the authors detail a clear-cut business model to help leaders take part in this coming boom; the AHEAD model outlines five strategic initiatives—Automate, Halos, Enhance, Abundance, and Discovery—that are central to competing in the next phase of global business by driving new levels of efficiency, customer intimacy and innovation.
Business leaders today have two options: be swallowed up by the ongoing technological evolution, or ride the crest of the wave to new profits and better business. This book shows you how to avoid your own extinction event, and will help you;
- Understand the untold full extent of technology's impact on the way we work and live.
- Find out where we're headed, and how soon the future will arrive
- Leverage the new emerging paradigm into a sustainable business advantage
- Adopt a strategic model for winning in the new economy
The digital world is already transforming how we work, live, and shop, how we are governed and entertained, and how we manage our money, health, security, and relationships. Don't let your business—or your career—get left behind. What To Do When Machines Do Everything is your strategic roadmap to a future full of possibility and success. Or peril.
- Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business
- Rise of the Robots: Technology and the Threat of a Jobless Future
- The EQ Leader: Instilling Passion, Creating Shared Goals, and Building Meaningful Organizations through Emotional Intelligence
- Modern Monopolies: What It Takes to Dominate the 21st Century Economy
- If You're in a Dogfight, Become a Cat!: Strategies for Long-Term Growth (Columbia Business School Publishing)
- The Four: The Hidden DNA of Amazon, Apple, Facebook, and Google
- The 7 Secrets of Neuron Leadership: What Top Military Commanders, Neuroscientists, and the Ancient Greeks Teach Us about Inspiring Teams
- Only Humans Need Apply: Winners and Losers in the Age of Smart Machines
- Capacity: Create Laser Focus, Boundless Energy, and an Unstoppable Drive In Any Organization
- Machine, Platform, Crowd: Harnessing Our Digital Future
|Accelerated Spanish: Learn fluent Spanish with a proven accelerated learning system
Lowest new price: $35.00
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Author: Timothy Moser
Brand: Moser Timothy
If you’re like the majority of US high school graduates, you have (1) studied Spanish at some point and (2) already forgotten most of it.
It’s time for a new language-learning method: One that teaches Spanish the way native speakers talk, using advanced mnemonic techniques you won’t be able to forget.
Accelerated Spanish is the proven method that has trained hundreds of students, bringing dozens to fluency in a very short period of time.
This three-volume system has the potential to make you fully fluent in Spanish.
- Volume One teaches you to think like a native Spanish speaker and gives you the vocabulary that makes up 50% of the Spanish language.
- Volume Two builds on that foundation, giving you 80% of the vocabulary, and it allows you to converse comfortably on a variety of subjects.
- Volume Three enables you to reach practical fluency in Spanish, enough to have an intelligent conversation with a native speaker on nearly any subject.
As you find yourself engulfed in an imaginary world with a yellow sky, demented shopkeepers, and clumsy stuffed pandas, your mind and senses will be challenged at every moment. From the very first chapter, you will begin to understand why truly getting into the mindset of another language requires your mind to experience a new world.
Timothy Moser is an accelerated learning expert and Spanish coach. In 2014 he founded Master of Memory, a leading online accelerated learning center. Timothy hosts 3 top-ranked podcasts, including Accelerated Spanish, where he applies advanced learning techniques to languages, inspiring and empowering listeners to learn Spanish and achieve fluency in a language for free. His course, Accelerated Spanish, is the only online Spanish coaching program that guarantees Spanish fluency.
“I was able to have hour-long conversations with native speakers and read almost any text in Spanish with no problem within 8 weeks. Highly recommended!” - Raghav H.
- Accelerated Spanish Learn Fluent Spanish with a Proven Accelerated Learning System
|Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)
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Author: Ian H. Witten
Brand: Morgan Kaufmann
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at http://www.cs.waikato.ac.nz/ml/weka/book.html
- Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
- Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
- Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
- Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
- Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
- Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
- Includes open-access online courses that introduce practical applications of the material in the book
|Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
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Author: Nikhil Buduma
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
- Understand the fundamentals of reinforcement learning
- Fundamentals of Deep Learning Designing Next Generation Machine Intelligence Algorithms
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