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Programming Languages -> PythonSearch on Amazon


Apprendre a programmer avec Python
Author: Gerard Swinnem  Language:
Contents: Penser comme un programmeur; Premiers pas; Contrôle du flux d'instructions; Instructions répétitives; Principaux types de données; Fonctions prédéfinies; Fonctions originales; Utilisation . . . . .
Dive Into Python
Author: Mark Pilgrim  Language:
Dive Into Python Dive Into Python is a Python book for experienced programmers. You can buy a printed copy, read it online, or download it in a variety of formats. It is also available in multiple languages.
Python for Econometrics
Author: Kevin Sheppard  Language:
Python for Econometrics Python is a widely used general purpose programming language, which happens to be well suited to Econometrics and other more general purpose data analysis tasks. These notes provide an introduction to . . . . .
How to Think Like a Computer Scientist: Learning with Python
Author: Allen Downey, Jeff Elkner and Chris Meyers.   Language:
How to Think Like a Computer Scientist:  Learning with Python How to Think... is an introduction to programming using Python, one of the best languages for beginners.
Think Python: How to Think Like a Computer Scientist
Author: Allen B. Downey  Language:
Think Python: How to Think Like a Computer Scientist Think Python is an introduction to Python programming for beginners. It starts with basic concepts of programming, and is carefully designed to define all terms when they are first used and to develop . . . . .
Think Complexity
Author: Allen B. Downey   Language:
Think Complexity This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science.
Think Stats: Probability and Statistics for Programmers
Author: Allen B. Downey  Language:
Think Stats: Probability and Statistics for Programmers Think Stats is an introduction to Probability and Statistics for Python programmers.
Numeric Python
Author: D Ascher, P. F. Dubois, K. Hinsen, J. Hugunin, T. Oli  Language:
The Numeric Python extensions (NumPy henceforth) is a set of extensions to the Python programming language which allows Python programmers to efficiently manipulate large sets of objects organized in . . . . .
Python for Education
Author: Ajith Kumar B.P.  Language:
In the first chapter, a general introduction ab out computers and high level programming languages is given. Basics of Python language, Python mo dules for array and matrix manipulation, 2D and 3D d . . . . .
Python High Performance Programming
Author: Lanaro, Gabriele  Language:
Contents: Benchmarking and Profiling; Fast Array Operations with NumPy; C Performance with Cython; Parallel Processing.
High Performance Python
Author: Ian Ozsvald  Language:
High Performance Python (from Training at EuroPython 2011)
A Quick, Painless Tutorial on the Python Language
Author: Norm Matloff  Language:
Contents: Overview; How to Use This Tutorial; A 5-Minute Introductory Example; A 10-Minute Introductory Example; Declaration (or Not), Scope, Functions, Etc. 13; A Couple of Built-In Functions; Types . . . . .
Python Tutorial
Author: python-docs@python.org  Language:
This tutorial introduces the reader informally to the basic concepts and features of the Python language and system. It helps to have a Python interpreter handy for hands-on experience, but all exampl . . . . .
How to Think Like a Computer Scientist
Author: Allen Downey Jerey Elkner Chris Meyers  Language:
How to Think Like a Computer Scientist How to Think Like a Computer Scientist. A guide to Python, 288 pp.
Text Processing in Python
Author: by David Mertz  Language:
Text Processing in Python This book is ideally suited for programmers who are a little bit familiar with Python, and whose daily tasks involve a fair amount of text processing chores. Programmers who have some backgr . . . . .
Problem Solving with Algorithms and Data Structures
Author: By Brad Miller and David Ranum, Luther College  Language:
Problem Solving with Algorithms and Data Structures Contents: Introduction; Analysis; Basic Data Structures; Recursion; Sorting and Searching; Trees and Tree Agorithms; Graphs and Graph Algorithms.

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