Coop UQAM | Coopsco

Créer mon profil | Mot de passe oublié?

Magasiner par secteur

Matériel obligatoire et recommandé

Voir les groupes
Devenir membre

Nos partenaires

UQAM
ESG UQAM
Réseau ESG UQAM
Bureau des diplômés
Centre sportif
Citadins
Service de la formation universitaire en région
Université à distance
Société de développement des entreprises culturelles - SODEC
L'institut du tourisme et de l'hotellerie - ITHQ
Pour le rayonnement du livre canadien
Presses de l'Université du Québec
Auteurs UQAM : Campagne permanente de promotion des auteures et auteurs UQAM
Fondation de l'UQAM
Écoles d'été en langues de l'UQAM
Canal savoir
L'économie sociale, j'achète
Millénium Micro



Recherche avancée...

Python Algorithms : Mastering Basic Algorithms in the Python Lang

Magnus, Lie Hetland


Éditeur : APRESS
ISBN papier: 9781430232377
Parution : 2010
Code produit : 1134760
Catégorisation : Livres / Science / Mathématique / Mathématiques

Formats disponibles

Format Qté. disp. Prix* Commander
Livre papier En rupture de stock** Prix membre : 52,20 $
Prix non-membre : 54,95 $
Telephone

*Les prix sont en dollars canadien. Taxes et frais de livraison en sus.
**Ce produits est en rupture de stock mais sera expédié dès qu'ils sera disponible.




Description

Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. * The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. * The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. * Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself. What you’ll learn * Transform new problems to well-known algorithmic problems with efficient solutions, or show that the problems belong to classes of problems thought not to be efficiently solvable. * Analyze algorithms and Python programs both using mathematical tools and basic experiments and benchmarks. * Prove correctness, optimality, or bounds on approximation error for Python programs and their underlying algorithms. * Understand several classical algorithms and data structures in depth, and be able to implement these efficiently in Python. * Design and implement new algorithms for new problems, using time-tested design principles and techniques. * Speed up implementations, using a plethora of tools for high-performance computing in Python. Who this book is for The book is intended for Python programmers who need to learn about algorithmic problem-solving, or who need a refresher. Students of Computer Science, or similar programming-related topics, such as bioinformatics, may also find the book to be quite useful.