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Algorithms in a Nutshell by Gary Pollice; Stanley Selkow; George T. HeinemanCreating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. This updated edition of Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs; with just enough math to let you understand and analyze algorithm performance.
Publication Date: 2016
Cloud Application Architectures by George ReeseIf you're involved in planning IT infrastructure as a network or system architect, system administrator, or developer, this book will help you adapt your skills to work with these highly scalable, highly redundant infrastructure services.
Nine Algorithms That Changed the Future: the Ingenious Ideas That Drive Today's Computers by John MacCormickUploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers; and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease? This is the first book to answer that question in language anyone can understand, revealing the extraordinary ideas that power our PCs, laptops, and smartphones.
Publication Date: 2012
Practical Malware Analysis by Michael Sikorski; Andrew HonigMalware analysis is big business, and attacks can cost a company dearly. When malware breaches your defenses, you need to act quickly to cure current infections and prevent future ones from occurring. For those who want to stay ahead of the latest malware, Practical Malware Analysis will teach you the tools and techniques used by professional analysts.
Publication Date: 2012
Software Engineering by Ian SommervilleIntended for introductory and advanced courses in software engineering. The ninth edition of Software Engineering presents a broad perspective of software engineering, focusing on the processes and techniques fundamental to the creation of reliable, software systems.
Publication Date: 2011
Selection of Ebooks in the Collection
97 Things Every Programmer Should Know by Kevlin Henney (Editor)Tap into the wisdom of experts to learn what every programmer should know, no matter what language you use. With the 97 short and extremely useful tips for programmers in this book, you'll expand your skills by adopting new approaches to old problems, learning appropriate best practices, and honing your craft through sound advice.
Publication Date: 2010
Computer Architecture by Gérard Blanchet; Bertrand DupouyThis book lays out the concepts necessary to understand how a computer works. For reasons of clarity, the authors have deliberately chosen examples that apply to machines from all eras, without having to water down the contents of the book. This choice helps to show how techniques, concepts and performances have evolved since the first computers.
Publication Date: 2013
Computer Networks by Andrew S. Tanenbaum; David J. WetherallTanenbaum takes a structured approach to explaining how networks work from the inside out. He starts with an explanation of the physical layer of networking, computer hardware and transmission systems; then works his way up to network applications.
Publication Date: 2017
Linux Bible by Christopher NegusThe industry favorite Linux guide, updated for Red Hat Enterprise Linux 7 and the cloud Linux Bible, 9th Edition is the ultimate hands-on Linux user guide, whether you're a true beginner or a more advanced user navigating recent changes. This updated ninth edition covers the latest versions of Red Hat Enterprise Linux 7 (RHEL 7), Fedora 21, and Ubuntu 14.04 LTS, and includes new information on cloud computing and development with guidance on Openstack and Cloudforms.
Publication Date: 2015
Python Data Analysis by Armando FandangoLearn how to apply powerful data analysis techniques with popular open source Python modules. An easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projects.
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