Bøker av Ben Klemens

This lively and innovative book is about computer code and the legal controls and restrictions on those who write it. The widespread use of personal computers and the Internet have made it possible to release new data or tools instantaneously to virtually the entire world.

Throw out your old ideas about C and get to know a programming language thats substantially outgrown its origins. With this revised edition of 21st Century C, youll discover up-to-date techniques missing from other C tutorials, whether youre new to the language or just getting reacquainted.C isnt just the foundation of modern programming languages; it is a modern language, ideal for writing efficient, state-of-the-art applications. Get past idioms that made sense on mainframes and learn the tools you need to work with this evolved and aggressively simple language. No matter what programming language you currently favor, youll quickly see that 21st century C rocks.Set up a C programming environment with shell facilities, makefiles, text editors, debuggers, and memory checkersUse Autotools, Cs de facto cross-platform package managerLearn about the problematic C concepts too useful to discardSolve Cs string-building problems with C-standard functionsUse modern syntactic features for functions that take structured inputsBuild high-level, object-based libraries and programsPerform advanced math, talk to internet servers, and run databases with existing C librariesThis edition also includes new material on concurrent threads, virtual tables, C99 numeric types, and other features.

Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date. Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.