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Canadiana

Canadiana PDF Author:
Publisher:
ISBN:
Category : Canada
Languages : en
Pages : 1020

Book Description


Canadiana

Canadiana PDF Author:
Publisher:
ISBN:
Category : Canada
Languages : en
Pages : 1020

Book Description


À vous de jouer : introduction à la science de l'informatique

À vous de jouer : introduction à la science de l'informatique PDF Author: Taurisson, Alain
Publisher:
ISBN: 9782891130264
Category : Electronic data processing
Languages : fr
Pages : 78

Book Description


Français Interactif

Français Interactif PDF Author: Karen Kelton
Publisher:
ISBN: 9781937963200
Category :
Languages : en
Pages :

Book Description
This textbook includes all 13 chapters of Français interactif. It accompanies www.laits.utexas.edu/fi, the web-based French program developed and in use at the University of Texas since 2004, and its companion site, Tex's French Grammar (2000) www.laits.utexas.edu/tex/ Français interactif is an open acess site, a free and open multimedia resources, which requires neither password nor fees. Français interactif has been funded and created by Liberal Arts Instructional Technology Services at the University of Texas, and is currently supported by COERLL, the Center for Open Educational Resources and Language Learning UT-Austin, and the U.S. Department of Education Fund for the Improvement of Post-Secondary Education (FIPSE Grant P116B070251) as an example of the open access initiative.

À vous de jouer : introduction à la science de l'informatique. Guide du maître

À vous de jouer : introduction à la science de l'informatique. Guide du maître PDF Author: Petitguillaume, André
Publisher: Mont-Royal, Québec : Modulo
ISBN: 9782891130578
Category : Electronic data processing
Languages : fr
Pages : 300

Book Description


Predicting Structured Data

Predicting Structured Data PDF Author: Neural Information Processing Systems Foundation
Publisher: MIT Press
ISBN: 0262026171
Category : Algorithms
Languages : en
Pages : 361

Book Description
State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

The Little Prince

The Little Prince PDF Author: Antoine de Saint−Exupery
Publisher: Aegitas
ISBN: 0369406370
Category : Young Adult Fiction
Languages : en
Pages : 102

Book Description
The Little Prince and nbsp;(French: and nbsp;Le Petit Prince) is a and nbsp;novella and nbsp;by French aristocrat, writer, and aviator and nbsp;Antoine de Saint-Exupéry. It was first published in English and French in the US by and nbsp;Reynal and amp; Hitchcock and nbsp;in April 1943, and posthumously in France following the and nbsp;liberation of France and nbsp;as Saint-Exupéry's works had been banned by the and nbsp;Vichy Regime. The story follows a young prince who visits various planets in space, including Earth, and addresses themes of loneliness, friendship, love, and loss. Despite its style as a children's book, and nbsp;The Little Prince and nbsp;makes observations about life, adults and human nature. The Little Prince and nbsp;became Saint-Exupéry's most successful work, selling an estimated 140 million copies worldwide, which makes it one of the and nbsp;best-selling and nbsp;and and nbsp;most translated books and nbsp;ever published. and nbsp;It has been translated into 301 languages and dialects. and nbsp;The Little Prince and nbsp;has been adapted to numerous art forms and media, including audio recordings, radio plays, live stage, film, television, ballet, and opera.

An Introduction to Computational Learning Theory

An Introduction to Computational Learning Theory PDF Author: Michael J. Kearns
Publisher: MIT Press
ISBN: 9780262111935
Category : Computers
Languages : en
Pages : 230

Book Description
Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.

The Nature of Statistical Learning Theory

The Nature of Statistical Learning Theory PDF Author: Vladimir Vapnik
Publisher: Springer Science & Business Media
ISBN: 1475732643
Category : Mathematics
Languages : en
Pages : 324

Book Description
The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.

Innovate Bristol

Innovate Bristol PDF Author: Sven Boermeester
Publisher:
ISBN: 9781949677072
Category :
Languages : en
Pages :

Book Description
Innovate Bristol highlights and celebrates those companies and individuals that are actively working at building a better tomorrow for all. Innovation Ecosystems thrive through the involvement and support of companies and individuals from all industries, which is why the Innovate series not only focuses on the innovators but also those people whom the Innovation Ecosystem, would not be able to thrive without.

Noncommutative Geometry

Noncommutative Geometry PDF Author: Alain Connes
Publisher: Springer
ISBN: 3540397027
Category : Mathematics
Languages : en
Pages : 364

Book Description
Noncommutative Geometry is one of the most deep and vital research subjects of present-day Mathematics. Its development, mainly due to Alain Connes, is providing an increasing number of applications and deeper insights for instance in Foliations, K-Theory, Index Theory, Number Theory but also in Quantum Physics of elementary particles. The purpose of the Summer School in Martina Franca was to offer a fresh invitation to the subject and closely related topics; the contributions in this volume include the four main lectures, cover advanced developments and are delivered by prominent specialists.