libristo introduction to college mathematics with a programming language 2187010
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Implementing Programming Languages. An Introduction to Compilers and Interpreters College Publications
Książki / Literatura obcojęzyczna
Implementing a programming language means bridging the gap from the programmer's high-level thinking to the machine's zeros and ones. If this is done in an efficient and reliable way, programmers can concentrate on the actual problems they have to solve, rather than on the details of machines. But understanding the whole chain from languages to machines is still an essential part of the training of any serious programmer. It will result in a more competent programmer, who will moreover be able to develop new languages. A new language is often the best way to solve a problem, and less difficult than it may sound.This book follows a theory-based practical approach, where theoretical models serve as blueprint for actual coding. The reader is guided to build compilers and interpreters in a well-understood and scalable way. The solutions are moreover portable to different implementation languages. Much of the actual codeis automatically generated from a grammar of the language, by using the BNF Converter tool. The rest can be written in Haskell or Java, for which thebook gives detailed guidance, but with some adaptation also in C, C++, C#, or OCaml, which are supported by the BNF Converter.The main focus of the book is on standard imperative and functional languages: a subset of C++ and a subset of Haskell are the source languages, and Java Virtual Machine is the main target. Simple Intel x86 native code compilation is shown to complete the chain from language to machine. The last chapter leaves the standard paths and explores the space of language design ranging fromminimal Turing-complete languages to human-computer interaction in natural language.
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Primer on Scientific Programming with Python Springer-Verlag Berlin and Heidelberg GmbH & Co....
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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.§§From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. §§F. H. Wild III, Choice, Vol. 47 (8), April 2010§§Those of us who have learned scientific programming in Python 'on the streets' could be a little jealous of students who have the opportunity to take a course out of Langtangen's Primer."§ John D. Cook, The Mathematical Association of America, September 2011§§This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science.§ Alex Small, IEEE, CiSE Vol. 14 (2), March _ /April 2012 §§"This fourth edition is a§wonderful, inclusive textbook that covers pretty much everything one needs to§know to go from zero to fairly sophisticated scientific programming in Python..."§Joan Horvath, Computing Reviews, March§2015 §§
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Introduction to Deep Learning Using R APress
Książki / Literatura obcojęzyczna
Understand deep learning, the nuances of its different models, and where these models can be applied.The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. Introduction to Deep Learning Using R provides a theoretical and practical understanding of the models that perform these tasks by building upon the fundamentals of data science through machine learning and deep learning. This step-by-step guide will help you understand the disciplines so that you can apply the methodology in a variety of contexts. All examples are taught in the R statistical language, allowing students and professionals to implement these techniques using open source tools.What You'll LearnUnderstand the intuition and mathematics that power deep learning modelsUtilize various algorithms using the R programming language and its packagesUse best practices for experimental design and variable selectionPractice the methodology to approach and effectively solve problems as a data scientistEvaluate the effectiveness of algorithmic solutions and enhance their predictive powerWho This Book Is ForStudents, researchers, and data scientists who are familiar with programming using R. This book also is also of use for those who wish to learn how to appropriately deploy these algorithms in applications where they would be most useful.
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Introduction to Data Analysis in R Springer Nature Switzerland AG
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This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.
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Introduction to Lambada Calculi for Computer Scientists Kings College Publications
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The lambda-calculus lies at the very foundations of computerscience. Besides its historical role in computability theory it hashad significant influence on programming language design andimplementation, denotational semantics, and domain theory. The bookemphasises the proof theory for the type-free lambda-calculus. Thefirst six chapters concern this calculus and cover the basic theory,reduction, models, computability, and the relationship between thelambda-calculus and combinatory logic. Chapter 7 presents a varietyof typed calculi; first the simply typed lambda-calculus, thenMilner-style polymorphism and, finally, the polymorphiclambda-calculus. Chapter 8 concerns two variants of the type-freelambda-calculus that have appeared in the research literature: thelazy lambda-calculus, and the lambda sigma-calculus. The finalchapter contains references and a guide to further reading. There areexercises throughout. In contrast to earlier books on these topics,which were written by logicians, this book is written from a computerscience perspective and emphasises the practical relevance of many ofthe key theoretical ideas. The book is intended as a course text forfinal year undergraduates or first year graduate students in computerscience. Research students should find it a useful introduction tomore specialist literature.
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Beautiful Code O'Reilly Media
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How do the experts solve difficult problems in software development? In this unique and insightful book, leading computer scientists offer case studies that reveal how they found unusual, carefully designed solutions to high-profile projects. You will be able to look over the shoulder of major coding and design experts to see problems through their eyes. This is not simply another design patterns book, or another software engineering treatise on the right and wrong way to do things. The authors think aloud as they work through their project's architecture, the tradeoffs made in its construction, and when it was important to break rules. "Beautiful Code" is an opportunity for master coders to tell their story. All author royalties will be donated to Amnesty International. The book includes the following contributions: "Beautiful Brevity: Rob Pike's Regular Expression Matcher" by Brian Kernighan, Department of Computer Science, Princeton University; "Subversion's Delta Editor: Interface as Ontology" by Karl Fogel, editor of "QuestionCopyright.org", Co-founder of Cyclic Software, the first company offering commercial CVS support; "The Most Beautiful Code I Never Wrote" by Jon Bentley, Avaya Labs Research; "Finding Things" by Tim Bray, Director of Web Technologies at Sun Microsystems, co-inventor of XML 1.0; "Correct, Beautiful, Fast (In That Order): Lessons From Designing XML Validators" by Elliotte Rusty Harold, Computer Science Department at Polytechnic University, author of "Java I/O, Java Network Programming", and "XML in a Nutshell" (O'Reilly); and, "The Framework for Integrated Test: Beauty through Fragility" by Michael Feathers, consultant at Object Mentor, author of "Working Effectively with Legacy Code" (Prentice Hall). It also includes: "Beautiful Tests" by Alberto Savoia, Chief Technology Officer, Agitar Software Inc; "On-the-Fly Code Generation for Image Processing" by Charles Petzold, author "Programming Windows and Code: The Hidden Language of Computer Hardware and Software" (both Microsoft Press); "Top Down Operator Precedence" by Douglas Crockford, architect at Yahoo!Inc, Founder and CTO of State Software, where he discovered JSON; "Accelerating Population Count" by Henry Warren, currently works on the Blue Gene petaflop computer project Worked for IBM for 41 years; "Secure Communication: The Technology of Freedom" by Ashish Gulhati, Chief Developer of Neomailbox, an Internet privacy service Developer of Cryptonite, an OpenPGP-compatible secure webmail system; and, "Growing Beautiful Code in BioPerl" by Lincoln Stein, investigator at Cold Spring Harbor Laboratory - develops databases and user interfaces for the Human Genome Project using the Apache server and its module API.It also includes: "The Design of the Gene Sorter" by Jim Kent, Genome Bioinformatics Group, University of California Santa Cruz; "How Elegant Code Evolves With Hardware: The Case Of Gaussian Elimination" by Jack Dongarra, University Distinguished Professor of Computer Science in the Computer Science Department at the University of Tennessee, also distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) and Piotr Luszczek, Research Professor at the University of Tennessee; "Beautiful Numerics" by Adam Kolawa, co-founder and CEO of Parasoft; and, "The Linux Kernel Driver Model" by Greg Kroah-Hartman, SuSE Labs/Novell, Linux kernel maintainer for driver subsystems, author of "Linux Kernel in a Nutshell", co-author of "Linux Device Drivers, 3rd Edition" (O'Reilly).It also includes: "Another Level of Indirection" by Diomidis Spinellis, Associate Professor at the Department of Management Science and Technology at the Athens University of Economics and Business, Greece; "An Examination of Python's Dictionary Implementation" by Andrew Kuchling, longtime member of the Python development community, and a director of the Python Software Foundation; "Multi-Dimensional Iterators in NumPy" by Travis Oliphant, Assistant Professor in the Electrical and Computer Engineering Department at Brigham Young University; and, "A Highly Reliable Enterprise System for NASAs Mars Rover Mission" by Ronald Mak, co-founder and CTO of Willard & Lowe Systems, Inc, formerly a senior scientist at the Research Institute for Advanced Computer Science on contract to NASA Ames.It also includes: "ERP5: Designing for Maximum Adaptability" by Rogerio de Carvalho, researcher at the Federal Center for Technological Education of Campos (CEFET Campos), Brazil and Rafael Monnerat, IT Analyst at CEFET Campos, and an offshore consultant for Nexedi SARL; "A Spoonful of Sewage" by Bryan Cantrill, Distinguished Engineer at Sun Microsystems, where he has spent most of his career working on the Solaris kernel; "Distributed Programming with MapReduce" by Jeff Dean and Sanjay Ghemawat, Google Fellows in Google's Systems Infrastructure Group; "Beautiful Concurrency" by Simon Peyton Jones, Microsoft Research, key contributor to the design of the functional language Haskell, and lead designer of the Glasgow Haskell Compiler (GHC); and, "Syntactic Abstraction: The syntax-case expander" by Kent Dybvig, Developer of Chez Scheme and author of the Scheme Programming Language. It also includes: "Object-Oriented Patterns and a Framework for Networked Software" by William Otte, a Ph.D. student in the Department of Electrical Engineering and Computer Science (EECS) at Vanderbilt University and Doug Schmidt, Full Professor in the Electrical Engineering and Computer Science (EECS) Department, Associate Chair of the Computer Science and Engineering program, and a Senior Research Scientist at the Institute for Software Integrated Systems (ISIS) at Vanderbilt University; "Integrating Business Partners the RESTful Way" by Andrew Patzer, Director of the Bioinformatics Program at the Medical College of Wisconsin; and, "Beautiful Debugging" by Andreas Zeller, computer science professor at Saarland University, author of "Why Programs Fail: A Guide to Systematic Debugging" (Morgan Kaufman).It also includes: "Code That's Like an Essay" by Yukihiro Matsumoto, inventor of the Ruby language; "Designing Interfaces Under Extreme Constraints: the Stephen Hawking editor" by Arun Mehta, professor and chairman of the Computer Engineering department of JMIT, Radaur, Haryana, India; "Emacspeak: The Complete Audio Desktop" by TV Raman, Research Scientist at Google where he focuses on web applications; "Code in Motion" by Christopher Seiwald, founder and CTO of Perforce Software and Laura Wingerd, vice president of product technology at Perforce Software, author of "Practical Perforce" (O'Reilly); and, "Writing Programs for 'The Book'" by Brian Hayes who writes the Computing Science column in American Scientist magazine, author of "Infrastructure: A Field Guide to the Industrial Landscape"(W.W. Norton).
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Learn Prolog Now! College Publications
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Prolog is a programming language, but a rather unusual one. ``Prolog'' is shortfor ``Programming with Logic'', and the link with logic gives Prolog itsspecial character. At the heart of Prolog lies a surprising idea: don't tellthe computer what to do. Instead, describe situations of interest, and computeby asking questions. Prolog will logically deduce new facts about thesituations and give its deductions back to us as answers.Why learn Prolog? For a start, its ``say what the problem is, rather than howto solve it'' stance, means that it is a very high level language, good forknowledge rich applications such as artificial intelligence, natural languageprocessing, and the semantic web. So by studying Prolog, you gain insight intohow sophisticated tasks can be handled computationally. Moreover, Prologrequires a different mindset. You have to learn to see problems from a newperspective, declaratively rather than procedurally.Acquiring this mindset, and learning to appreciate the links between logic andprogramming, makes the study of Prolog both challenging and rewarding.Learn Prolog Now! is a practical introduction to this fascinatinglanguage. Freely available as a web-book since 2002 (seewww.learnprolognow.org) Learn Prolog Now! has became one of the mostpopular introductions to the Prolog programming language, an introductionprized for its clarity and down-to-earth approach. It is widely used as atextbook at university departments around the world, and even more widely usedfor self study.College Publications is proud to present here the first hard-copy version ofthis online classic. Carefully revised in the light of reader's feedback, andnow with answers to all the exercises, here you will find the essentialmaterial required to help you learn Prolog now.
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Learning to Program with MATLAB - Building GUI Tools, Second Edition John Wiley and Sons Ltd
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Learning to Program with MATLABIntroductory text integrating science, mathematics, and engineering to give a basic understanding of the fundamentals of computer programming with MATLABLearning to Program with MATLAB: Building GUI Tools, Second Edition serves as a compact introduction to computer programming using the MATLAB language, covering elements of both program and graphical user interface (GUI) design to enable readers to create computer programs just like the ones they are accustomed to interacting with. Rather than being encyclopedic in scope, the goal of the text is to describe what users will find most useful and point to other features. Descriptions and examples of some of the most useful functions are included throughout, particularly with regards to engineering and science applications. The work also includes updated videos and problem solutions on an instructor companion website.The first edition of Learning to Program with MATLAB employed the MATLAB graphical user interface design environment (GUIDE) to develop the GUI tools. The second edition is based on the new and improved App Designer program, which has supplanted GUIDE. This edition includes:* Core concepts of computer programming using MATLAB, such as arrays, loops, functions, and basic data structures* How to write your own MATLAB functions, covering topics such as local workspaces, multiple outputs, function files, and other functional forms* The new string class and table class, some new features of function arguments, and re-written sections for building GUI tools with App Designer* Syntax for graphics and App Designer features, plus examples demonstrating the new way to handle string informationStarting with the basics and building up to an emphasis on GUI tools, Learning to Program with MATLAB is a comprehensive introduction to programming in a robust and multipurpose language, making it an ideal classroom resource for both students and instructors in related programs of study.
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Big R-Book - From Data Science to Learning Machines and Big Data John Wiley and Sons Ltd
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Introduces professionals and scientists to statistics and machine learning using the programming language R Written by and for practitioners, this book provides an overall introduction to R, focusing on tools and methods commonly used in data science, and placing emphasis on practice and business use. It covers a wide range of topics in a single volume, including big data, databases, statistical machine learning, data wrangling, data visualization, and the reporting of results. The topics covered are all important for someone with a science/math background that is looking to quickly learn several practical technologies to enter or transition to the growing field of data science. The Big R-Book for Professionals: From Data Science to Learning Machines and Reporting with R includes nine parts, starting with an introduction to the subject and followed by an overview of R and elements of statistics. The third part revolves around data, while the fourth focuses on data wrangling. Part 5 teaches readers about exploring data. In Part 6 we learn to build models, Part 7 introduces the reader to the reality in companies, Part 8 covers reports and interactive applications and finally Part 9 introduces the reader to big data and performance computing. It also includes some helpful appendices. * Provides a practical guide for non-experts with a focus on business users * Contains a unique combination of topics including an introduction to R, machine learning, mathematical models, data wrangling, and reporting * Uses a practical tone and integrates multiple topics in a coherent framework * Demystifies the hype around machine learning and AI by enabling readers to understand the provided models and program them in R * Shows readers how to visualize results in static and interactive reports * Supplementary materials includes PDF slides based on the book's content, as well as all the extracted R-code and is available to everyone on a Wiley Book Companion Site The Big R-Book is an excellent guide for science technology, engineering, or mathematics students who wish to make a successful transition from the academic world to the professional. It will also appeal to all young data scientists, quantitative analysts, and analytics professionals, as well as those who make mathematical models.
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Algorithms with JULIA Springer, Berlin
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This book provides an introduction to modern topics in scientific computing, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (supervised and unsupervised learning). JULIA is a relatively new programming language which has developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system. Aimed at students of applied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming.
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Good Math The Pragmatic Programmers
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Mathematics is beautiful--and it can be fun and exciting as well as practical. Good Math is your guide to some of the most intriguing topics from two thousand years of mathematics: from Egyptian fractions to Turing machines; from the real meaning of numbers to proof trees, group symmetry, and mechanical computation. If you've ever wondered what lay beyond the proofs you struggled to complete in high school geometry, or what limits the capabilities of computer on your desk, this is the book for you. Why do Roman numerals persist? How do we know that some infinities are larger than others? And how can we know for certain a program will ever finish? In this fast-paced tour of modern and not-so-modern math, computer scientist Mark Chu-Carroll explores some of the greatest breakthroughs and disappointments of more than two thousand years of mathematical thought. There is joy and beauty in mathematics, and in more than two dozen essays drawn from his popular "Good Math" blog, you'll find concepts, proofs, and examples that are often surprising, counterintuitive, or just plain weird.Mark begins his journey with the basics of numbers, with an entertaining trip through the integers and the natural, rational, irrational, and transcendental numbers. The voyage continues with a look at some of the oddest numbers in mathematics, including zero, the golden ratio, imaginary numbers, Roman numerals, and Egyptian and continuing fractions. After a deep dive into modern logic, including an introduction to linear logic and the logic-savvy Prolog language, the trip concludes with a tour of modern set theory and the advances and paradoxes of modern mechanical computing. If your high school or college math courses left you grasping for the inner meaning behind the numbers, Mark's book will both entertain and enlighten you.
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Decision Optimization with IBM ILOG CPLEX Optimization Studio Springer, Berlin
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This textbook offers a comprehensive, up-to-date introduction to the Optimization Programming Language (OPL). Embedded in the IBM ILOG CPLEX Optimization Studio with its solver engine CPLEX, OPL has been popular for years not only for academic and scientific purposes, but also among practitioners who need to model and solve large-scale real-world business optimization problems. The book covers the recent features of the software and includes ten consecutive tutorials, each with additional exercises, as well as several comprehensive application studies.The book is specifically designed for advanced undergraduate and graduate courses in e.g. management science, operations research, computer science, mathematics, mathematical economics, and industrial engineering. It can also serve as self-study material for practitioners whose work involves the modeling and optimization of planning and decision problems and who need a sound introduction to the software.Solutions to the exercises as well as the source codes from the textbook are available for download (weblink included).
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Book of Proof Richard Hammack
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This book is an introduction to the language and standard proof methods of mathematics. It is a bridge from the computational courses (such as calculus or differential equations) that students typically encounter in their first year of college to a more
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Book of Proof Richard Hammack
Książki / Literatura obcojęzyczna
This book is an introduction to the language and standard proof methods of mathematics. It is a bridge from the computational courses (such as calculus or differential equations) that students typically encounter in their first year of college to a more
Sklep: Libristo.pl
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