Natural Language Processing with Python


Steven Bird - 2009
    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 intelligenceThis 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.

Learn Python 3 the Hard Way: A Very Simple Introduction to the Terrifyingly Beautiful World of Computers and Code (Zed Shaw's Hard Way Series)


Zed A. Shaw - 2017
    

Processing: A Programming Handbook for Visual Designers and Artists


Casey Reas - 2007
    This book is an introduction to the concepts of computer programming within the context of the visual arts. It offers a comprehensive reference and text for Processing (www.processing.org), an open-source programming language that can be used by students, artists, designers, architects, researchers, and anyone who wants to program images, animation, and interactivity. The ideas in Processing have been tested in classrooms, workshops, and arts institutions, including UCLA, Carnegie Mellon, New York University, and Harvard University. Tutorial units make up the bulk of the book and introduce the syntax and concepts of software (including variables, functions, and object-oriented programming), cover such topics as photography and drawing in relation to software, and feature many short, prototypical example programs with related images and explanations. More advanced professional projects from such domains as animation, performance, and typography are discussed in interviews with their creators. "Extensions" present concise introductions to further areas of investigation, including computer vision, sound, and electronics. Appendixes, references to additional material, and a glossary contain additional technical details. Processing can be used by reading each unit in order, or by following each category from the beginning of the book to the end. The Processing software and all of the code presented can be downloaded and run for future exploration.Includes essays by Alexander R. Galloway, Golan Levin, R. Luke DuBois, Simon Greenwold, Francis Li, and Hernando Barragan and interviews with Jared Tarbell, Martin Wattenberg, James Paterson, Erik van Blockland, Ed Burton, Josh On, Jurg Lehni, Auriea Harvey and Michael Samyn, Mathew Cullen and Grady Hall, Bob Sabiston, Jennifer Steinkamp, Ruth Jarman and Joseph Gerhardt, Sue Costabile, Chris Csikszentmihalyi, Golan Levin and Zachary Lieberman, and Mark Hansen.Casey Reas is Associate Professor in the Design Media Arts Department at the University of California, Los Angeles. Ben Fry is Nierenburg Chair of Design in the School of Design at Carnegie Mellon University, 2006-2007."

Persuasion Skills Black Book: Practical NLP Language Patterns for Getting the Response You Want


Rintu Basu - 2009
    The Persuasion Skills Black Book is a manual for quickly learning some very powerful hypnotic language patterns that you can use in practical, real world situations. These patterns are not necessarily about sending people into a hypnotic trance but just a way to move you from one perspective on an issue to another. By the book's end you will have the structures in place to make more money, attract more people and have more fun. Just some of the applications include: Managers: powerfully motivate your teams Leaders: inspire people to your vision Parents: protect and encourage your children Teachers: get your classes to commit to learning Coaches: build client confidence and commitment Sales Pros: obliterate objections and get to 'yes' Marketers: boost your response with compelling copy Couples: strengthen and build your relationship Singles: attract and impress potential partners Employees: manage your boss and gain promotions Customers: get your complaints handled properly Service Staff: turn angry customers into best friends Job Seekers: ace interviews and win the job you want All of us: get more of what you want from life What new opportunities open up to you when you can persuade others to do what you want, easily and effortlessly, in any situation? Acclaimed NLP trainer, Rintu Basu, has worked hard to devise this book so that you don't have to. As well as clearly laid-out chapters, examples and case studies, the whole book has been written using the very patterns you'll be learning. So, as you read and use your new skills, your conscious understanding and unconscious ability will continue to deepen.

57 Ways to Screw Up in Grad School: Perverse Professional Lessons for Graduate Students


Kevin D. Haggerty - 2015
    Select a topic for entirely strategic reasons. Choose the coolest supervisor. Write only to deadlines. Expect people to hold your hand. Become “that” student. When it comes to a masters or PhD program, most graduate students don’t deliberately set out to  fail. Yet, of the nearly 500,000 people who start a graduate program each year, up to half will never complete their degree. Books abound on acing the admissions process, but there is little on what to do once the acceptance letter arrives. Veteran graduate directors Kevin D. Haggerty and Aaron Doyle have set out to demystify the world of advanced education. Taking a wry, frank approach, they explain the common mistakes that can trip up a new graduate student and lay out practical advice about how to avoid the pitfalls. Along the way they relate stories from their decades of mentorship and even share some slip-ups from their own grad experiences. The litany of foul-ups is organized by theme and covers the grad school experience from beginning to end: selecting the university and program, interacting with advisors and fellow students, balancing personal and scholarly lives, navigating a thesis, and creating a life after academia. Although the tone is engagingly tongue-in-cheek, the lessons are crucial to anyone attending or contemplating grad school. 57 Ways to Screw Up in Grad School allows you to learn from others’ mistakes rather than making them yourself.

Think Complexity: Complexity Science and Computational Modeling


Allen B. Downey - 2009
    Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations.You’ll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise.Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tablesStudy abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machinesGet starter code and solutions to help you re-implement and extend original experiments in complexityExplore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topicsExamine case studies of complex systems submitted by students and readers

Modern Information Retrieval


Ricardo Baeza-Yates - 1999
    The timely provision of relevant information with minimal 'noise' is critical to modern society and this is what information retrieval (IR) is all about. It is a dynamic subject, with current changes driven by the expansion of the World Wide Web, the advent of modern and inexpensive graphical user interfaces and the development of reliable and low-cost mass storage devices. Modern Information Retrieval discusses all these changes in great detail and can be used for a first course on IR as well as graduate courses on the topic.The organization of the book, which includes a comprehensive glossary, allows the reader to either obtain a broad overview or detailed knowledge of all the key topics in modern IR. The heart of the book is the nine chapters written by Baeza-Yates and Ribeiro-Neto, two leading exponents in the field. For those wishing to delve deeper into key areas there are further state-of-the-art ch

The Little Go Book


Karl Seguin - 2014
    It's aimed at developers who might not be quite comfortable with the idea of pointers and static typing.http://openmymind.net/The-Little-Go-B...

Python for Data Analysis


Wes McKinney - 2011
    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

Microprocessors and Microcontrollers


N. Senthil Kumar - 2011
    It also touches upon the fundamentals of 32 bit, and 64 bit advanced processors. The book throughout provides the most popular programming tool - the assembly language codes to enhance the knowledge of programming the processors.Clear and concise in its treatment of topics, the contents of the book is supported by learning tools such as review questions, application examples (case studies) and design-based exercises.

Data Science at the Command Line: Facing the Future with Time-Tested Tools


Jeroen Janssens - 2014
    You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms

Taming Text: How to Find, Organize, and Manipulate It


Grant S. Ingersoll - 2011
    This causes real problems for everyday users who need to make sense of all the information available, and for software engineers who want to make their text-based applications more useful and user-friendly. Whether building a search engine for a corporate website, automatically organizing email, or extracting important nuggets of information from the news, dealing with unstructured text can be daunting.Taming Text is a hands-on, example-driven guide to working with unstructured text in the context of real-world applications. It explores how to automatically organize text, using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. This book gives examples illustrating each of these topics, as well as the foundations upon which they are built.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.

Programming: Principles and Practice Using C++


Bjarne Stroustrup - 2008
    Available here:blubbu.com/download?i=0321992784Programming: Principles and Practice Using C++ (2nd Edition) PDF by Bjarne Stroustrup

When the Rivers Run Dry: Water - The Defining Crisis of the Twenty-first Century


Fred Pearce - 2006
    Deftly weaving together the complicated scientific, economic, and historic dimensions of the world water crisis, he provides our most complete portrait yet of this growing danger and its ramifications for us all. Named as one of the Top 50 Sustainability Books by University of Cambridges Programme for Sustainability Leadership and Greenleaf Publishing.

C++ Coding Standards: 101 Rules, Guidelines, and Best Practices


Herb Sutter - 2004
    This happens automatically when following agood, simple set of guidelines.*They improve development speed, because the programmer doesn't need toalways make decisions starting from first principles.*They enhance teamwork by eliminating needless debates on inconsequentialissues and by making it easy for teammates to read and maintain each other'scode.The coding standards introduced by this book are a collection of guidelines forwriting high-quality C++ code.***They are the distilled conclusions of a rich collective experience of the C++community. Until now, this body of knowledge has been available only asfolklore or spread in bits and pieces throughout books.