This text provides a very simple, initial introduction to the complete scientific computing pipeline: models, discretization, algorithms, programming, verification, and visualization. The book is easy to read and only requires a command of one-variable calculus and some very basic knowledge about computer programming.
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This book introduces the most important ideas in computing using the Scheme and Python programming languages. It focuses on how to describe information processes by defining procedures, how to analyze the costs required to carry out a procedure, and the fundamental limits of what can and cannot be computed mechanically.
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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.
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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.
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This book is going to try to teach you the things about Unix development that Unix experts know, but aren’t aware that they know. It is therefore less about technicalia and more about shared culture than most Unix books – both explicit and implicit culture, both conscious and unconscious traditions.
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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…).
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Haskell is great and if you’re interested in programming you should really learn it even if it seems weird at first. Learning Haskell is much like learning to program for the first time — it’s fun! It forces you to think differently.
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While there have been already a lot of wonderful books about algorithms, data structures and math, however, few of them provide the comparison between the procedural solution and the functional solution. It can be found that functional solution sometimes is very expressive and they are close to what we are familiar in mathematics.
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