Book picks similar to
The C Programming Language by Brian W. Kernighan
programming
computer-science
non-fiction
reference
Concepts, Techniques, and Models of Computer Programming
Peter Van Roy - 2004
The book focuses on techniques of lasting value and explains them precisely in terms of a simple abstract machine. The book presents all major programming paradigms in a uniform framework that shows their deep relationships and how and where to use them together.After an introduction to programming concepts, the book presents both well-known and lesser-known computation models ("programming paradigms"). Each model has its own set of techniques and each is included on the basis of its usefulness in practice. The general models include declarative programming, declarative concurrency, message-passing concurrency, explicit state, object-oriented programming, shared-state concurrency, and relational programming. Specialized models include graphical user interface programming, distributed programming, and constraint programming. Each model is based on its kernel language—a simple core language that consists of a small number of programmer- significant elements. The kernel languages are introduced progressively, adding concepts one by one, thus showing the deep relationships between different models. The kernel languages are defined precisely in terms of a simple abstract machine. Because a wide variety of languages and programming paradigms can be modeled by a small set of closely related kernel languages, this approach allows programmer and student to grasp the underlying unity of programming. The book has many program fragments and exercises, all of which can be run on the Mozart Programming System, an Open Source software package that features an interactive incremental development environment.
Apprenticeship Patterns: Guidance for the Aspiring Software Craftsman
Dave Hoover - 2009
To grow professionally, you also need soft skills and effective learning techniques. Honing those skills is what this book is all about. Authors Dave Hoover and Adewale Oshineye have cataloged dozens of behavior patterns to help you perfect essential aspects of your craft. Compiled from years of research, many interviews, and feedback from O'Reilly's online forum, these patterns address difficult situations that programmers, administrators, and DBAs face every day. And it's not just about financial success. Apprenticeship Patterns also approaches software development as a means to personal fulfillment. Discover how this book can help you make the best of both your life and your career. Solutions to some common obstacles that this book explores in-depth include:Burned out at work? "Nurture Your Passion" by finding a pet project to rediscover the joy of problem solving.Feeling overwhelmed by new information? Re-explore familiar territory by building something you've built before, then use "Retreat into Competence" to move forward again.Stuck in your learning? Seek a team of experienced and talented developers with whom you can "Be the Worst" for a while. "Brilliant stuff! Reading this book was like being in a time machine that pulled me back to those key learning moments in my career as a professional software developer and, instead of having to learn best practices the hard way, I had a guru sitting on my shoulder guiding me every step towards master craftsmanship. I'll certainly be recommending this book to clients. I wish I had this book 14 years ago!" -Russ Miles, CEO, OpenCredo
Deep Learning with Python
François Chollet - 2017
It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.
Hadoop: The Definitive Guide
Tom White - 2009
Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!
Eloquent Ruby
Russ Olsen - 2011
In
Eloquent Ruby,
Russ Olsen helps you write Ruby like true Rubyists do-so you can leverage its immense, surprising power. Olsen draws on years of experience internalizing the Ruby culture and teaching Ruby to other programmers. He guides you to the "Ah Ha!" moments when it suddenly becomes clear why Ruby works the way it does, and how you can take advantage of this language's elegance and expressiveness.
Eloquent Ruby
starts small, answering tactical questions focused on a single statement, method, test, or bug. You'll learn how to write code that actually looks like Ruby (not Java or C#); why Ruby has so many control structures; how to use strings, expressions, and symbols; and what dynamic typing is really good for. Next, the book addresses bigger questions related to building methods and classes. You'll discover why Ruby classes contain so many tiny methods, when to use operator overloading, and when to avoid it. Olsen explains how to write Ruby code that writes its own code-and why you'll want to. He concludes with powerful project-level features and techniques ranging from gems to Domain Specific Languages. A part of the renowned Addison-Wesley Professional Ruby Series,
Eloquent Ruby
will help you "put on your Ruby-colored glasses" and get results that make you a true believer.
Python Data Science Handbook: Tools and Techniques for Developers
Jake Vanderplas - 2016
Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Problem Solving with C++: The Object of Programming
Walter J. Savitch - 1995
It introduces the use of classes; shows how to write ADTs that maximize the perfomance of C++ in creating reusable code; and provides coverage of all important OO functions, including inheritance, polymorphism and encapsulation.
The Psychology of Computer Programming
Gerald M. Weinberg - 1971
Weinberg adds new insights and highlights the similarities and differences between now and then. Using a conversational style that invites the reader to join him, Weinberg reunites with some of his most insightful writings on the human side of software engineering.Topics include egoless programming, intelligence, psychological measurement, personality factors, motivation, training, social problems on large projects, problem-solving ability, programming language design, team formation, the programming environment, and much more.Dorset House Publishing is proud to make this important text available to new generations of programmers -- and to encourage readers of the first edition to return to its valuable lessons.
The Art of Electronics
Paul Horowitz - 1980
Widely accepted as the authoritative text and reference on electronic circuit design, both analog and digital, this book revolutionized the teaching of electronics by emphasizing the methods actually used by circuit designers -- a combination of some basic laws, rules of thumb, and a large bag of tricks. The result is a largely nonmathematical treatment that encourages circuit intuition, brainstorming, and simplified calculations of circuit values and performance. The new Art of Electronics retains the feeling of informality and easy access that helped make the first edition so successful and popular. It is an ideal first textbook on electronics for scientists and engineers and an indispensable reference for anyone, professional or amateur, who works with electronic circuits.
Learning PHP, MySQL, and JavaScript: A Step-By-Step Guide to Creating Dynamic Websites
Robin Nixon - 2009
You'll learn how to create responsive, data-driven websites with PHP, MySQL, and JavaScript, regardless of whether you already know how to program. Discover how the powerful combination of PHP and MySQL provides an easy way to build modern websites complete with dynamic data and user interaction. You'll also learn how to add JavaScript to create rich Internet applications and websites.Learning PHP, MySQL, and JavaScript explains each technology separately, shows you how to combine them, and introduces valuable web programming concepts, including objects, XHTML, cookies, and session management. You'll practice what you've learned with review questions in each chapter, and find a sample social networking platform built with the elements introduced in this book. This book will help you:-Understand PHP essentials and the basics of object-oriented programming-Master MySQL, from database structure to complex queries-Create web pages with PHP and MySQL by integrating forms and other HTML features-Learn about JavaScript, from functions and event handling to accessing the Document Object Model-Use libraries and packages, including the Smarty web template system, PEAR program repository, and the Yahoo! User Interface Library -Make Ajax calls and turn your website into a highly dynamic environment-Upload and manipulate files and images, validate user input, and secure your applications
Head First Object-Oriented Analysis and Design: A Brain Friendly Guide to OOA&D
Brett McLaughlin - 2006
What sets this book apart is its focus on learning. The authors have made the content of OOAD accessible, usable for the practitioner." Ivar Jacobson, Ivar Jacobson Consulting"I just finished reading HF OOA&D and I loved it! The thing I liked most about this book was its focus on why we do OOA&D-to write great software!" Kyle Brown, Distinguished Engineer, IBM"Hidden behind the funny pictures and crazy fonts is a serious, intelligent, extremely well-crafted presentation of OO Analysis and Design. As I read the book, I felt like I was looking over the shoulder of an expert designer who was explaining to me what issues were important at each step, and why." Edward Sciore, Associate Professor, Computer Science Department, Boston College Tired of reading Object Oriented Analysis and Design books that only makes sense after you're an expert? You've heard OOA&D can help you write great software every time-software that makes your boss happy, your customers satisfied and gives you more time to do what makes you happy.But how?Head First Object-Oriented Analysis & Design shows you how to analyze, design, and write serious object-oriented software: software that's easy to reuse, maintain, and extend; software that doesn't hurt your head; software that lets you add new features without breaking the old ones. Inside you will learn how to:Use OO principles like encapsulation and delegation to build applications that are flexible Apply the Open-Closed Principle (OCP) and the Single Responsibility Principle (SRP) to promote reuse of your code Leverage the power of design patterns to solve your problems more efficiently Use UML, use cases, and diagrams to ensure that all stakeholders are communicating clearly to help you deliver the right software that meets everyone's needs.By exploiting how your brain works, Head First Object-Oriented Analysis & Design compresses the time it takes to learn and retain complex information. Expect to have fun, expect to learn, expect to be writing great software consistently by the time you're finished reading this!
Introduction to Computation and Programming Using Python
John V. Guttag - 2013
It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.
Core Java 2, Volume I--Fundamentals (Core Series)
Cay S. Horstmann - 1999
A no-nonsense tutorial and reliable reference, this book features thoroughly tested real-world examples. The most important language and library features are demonstrated with deliberately simple sample programs, but they aren't fake and they don't cut corners. More importantly, all of the programs have been updated for J2SE 5.0 and should make good starting points for your own code. You won't find any toy examples here. This is a book for programmers who want to write real code to solve real problems. Cay S. Horstmann is a professor of computer science at San Jose State University. Previously he was vice president and chief technology officer of Preview Systems Inc. and a consultant on C++, Java, and Internet programming for major corporations, universities, and organizations. Gary Cornell has written or cowritten more than twenty popular computer books. He has a Ph.D. from Brown University and has been a visiting scientist at IBM Watson Laboratories, as well as a professor at the University of Connecticut.
The C# Programming Yellow Book
Rob Miles - 2010
With jokes, puns, and a rigorous problem solving based approach. You can download all the code samples used in the book from here: http://www.robmiles.com/s/Yellow-Book...
JavaScript Patterns
Stoyan Stefanov - 2010
If you're an experienced developer looking to solve problems related to objects, functions, inheritance, and other language-specific categories, the abstractions and code templates in this guide are ideal -- whether you're writing a client-side, server-side, or desktop application with JavaScript.Written by JavaScript expert Stoyan Stefanov -- Senior Yahoo! Technical and architect of YSlow 2.0, the web page performance optimization tool -- JavaScript Patterns includes practical advice for implementing each pattern discussed, along with several hands-on examples. You'll also learn about anti-patterns: common programming approaches that cause more problems than they solve.Explore useful habits for writing high-quality JavaScript code, such as avoiding globals, using single var declarations, and moreLearn why literal notation patterns are simpler alternatives to constructor functionsDiscover different ways to define a function in JavaScriptCreate objects that go beyond the basic patterns of using object literals and constructor functionsLearn the options available for code reuse and inheritance in JavaScriptStudy sample JavaScript approaches to common design patterns such as Singleton, Factory, Decorator, and moreExamine patterns that apply specifically to the client-side browser environment