This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. Designed as a textbook for graduate-level algorithms courses, the book will also serve as a reference for researchers who are interested in the heuristic solution of discrete optimization problems.
Practical Common Lisp serves as a useful introduction to Common Lisp for folks who are curious about Lisp but maybe not yet curious enough to shell out big bucks for a dead-tree book and a good Common Lisp tutorial for folks who want to get down to real coding right away.
Think Stats is an introduction to Probability and Statistics for Python programmers. It emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health.
Algorithms, 4th Edition surveys the most important algorithms and data structures in use today. We motivate each algorithm that we address by examining its impact on applications to science, engineering, and industry.
This book will be useful for those in the scientific community who gather data and seek tools for analyzing and interpreting data. It will be a valuable reference for scientists in a variety of disciplines and can serve as a textbook for a graduate course in exploratory data analysis as well as a supplemental text in courses on research methodology, pattern recognition, image processing, and re-mote sensing.
Let Over Lambda is one of the most hardcore computer programming books out there. Starting with the fundamentals, it describes the most advanced features of the most advanced language: COMMON LISP. The point of this book is to expose you to ideas that you might otherwise never be exposed to.
You’ll begin your exploration in Python by understanding the key differences between Python 3 and the previous versions of the language. From there, you’ll set up a programming environment for your relevant local or server-based system, and begin by learning general Python code structure, syntax, and data types.
This online ebook wants itself to be a way to learn Erlang for people who have basic knowledge of programming in imperative languages (such as C/C++, Java, Python, Ruby, etc) and may or may not know functional programming (Haskell, Scala, Erlang, Clojure, OCaml…).
This is the 22 February 2013 version of Impatient Perl. This document is for people who either want to learn perl or are already programming in perl and just do not have the patience to scrounge for information to learn and use perl. This document should also find use as a handy desk reference for some of the more common perl related questions.