Book picks similar to
Complex Network Analysis in Python: Recognize - Construct - Visualize - Analyze - Interpret by Dmitry Zinoviev
programming
python
science
computer-science
Data Structures and Algorithms
Alfred V. Aho - 1983
Algorithm design techniques are also stressed and basic algorithm analysis is covered. Most of the programs are written in Pascal.
Numerical Recipes in C: The Art of Scientific Computing
William H. Press - 1988
In a self-contained manner it proceeds from mathematical and theoretical considerations to actual practical computer routines. With over 100 new routines bringing the total to well over 300, plus upgraded versions of the original routines, the new edition remains the most practical, comprehensive handbook of scientific computing available today.
The Basics of Digital Forensics: The Primer for Getting Started in Digital Forensics
John Sammons - 2011
This book teaches you how to conduct examinations by explaining what digital forensics is, the methodologies used, key technical concepts and the tools needed to perform examinations. Details on digital forensics for computers, networks, cell phones, GPS, the cloud, and Internet are discussed. Readers will also learn how to collect evidence, document the scene, and recover deleted data. This is the only resource your students need to get a jump-start into digital forensics investigations.This book is organized into 11 chapters. After an introduction to the basics of digital forensics, the book proceeds with a discussion of key technical concepts. Succeeding chapters cover labs and tools; collecting evidence; Windows system artifacts; anti-forensics; Internet and email; network forensics; and mobile device forensics. The book concludes by outlining challenges and concerns associated with digital forensics. PowerPoint lecture slides are also available.This book will be a valuable resource for entry-level digital forensics professionals as well as those in complimentary fields including law enforcement, legal, and general information security.
Mean Ol' Mr. Gravity
Mark Rippetoe - 2009
Gravity is a compilation of Q&A posts from Mark Rippetoe s StrengthMill forum. Edited for brevity, efficiency, clarity, accuracy, and taste (in a loose sense, sorry), Mean Ol' Mr. Gravity adds to the information available in Starting Strength: Basic Barbell Training and Practical Programming for Strength Training by tailoring it to the individual through his responses to questions posed by actual humans regarding their own training. It preserves the coarseness, humor, and candor that have become Rip s trademark style. A Question. Goombahboy: Hey Rip, why would you make a book out of a bunch of posts that are already available on the web? What could you possibly have been thinking? Mark Rippetoe: An excellent question. I have no idea, other than the fact that a book like this makes an excellent bathroom companion. The reading-kind of companion. Information and humor in small, easily managed chunks. Conveniently digestible pieces, as it were. Well, you know what I mean. Bozo1988: Yeah, what were you thinking? I mean, I know there s a lot of information here, I know that all of the really stupid stuff that would waste my time while reading it online has been removed, and that the videos posted on the board don t load very fast in a book format anyway, but why a book? Mark Rippetoe: Look, just read the damn thing, okay? You ll be fine.
Algorithms Illuminated (Part 1): The Basics
Tim Roughgarden - 2017
Their applications range from network routing and computational genomics to public-key cryptography and database system implementation. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subject---a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. The exposition is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. Part 1 of the book series covers asymptotic analysis and big-O notation, divide-and-conquer algorithms and the master method, randomized algorithms, and several famous algorithms for sorting and selection.