عنوان

Introduction to deep learning :

(Number (ISBN

3319730045

(Number (ISBN

9783319730042

Erroneous ISBN

3319730037

Erroneous ISBN

9783319730035

Country Code

bnb

Number

b624108

Title Proper

Introduction to deep learning :

General Material Designation

[Book]

Other Title Information

from logical calculus to artificial intelligence /

First Statement of Responsibility

Sandro Skansi.

Specific Material Designation and Extent of Item

1 online resource (XIII, 191 pages) :

Other Physical Details

38 illustrations

Series Title

Undergraduate Topics in Computer Science,

ISSN of Series

1863-7310

Text of Note

Includes bibliographical references and index.

Text of Note

From Logic to Cognitive Science -- Mathematical and Computational Prerequisites -- Machine Learning Basics -- Feed-forward Neural Networks -- Modifications and Extensions to a Feed-forward Neural Network -- Convolutional Neural Networks -- Recurrent Neural Networks -- Autoencoders -- Neural Language Models -- An Overview of Different Neural Network Architectures -- Conclusion.

0

Text of Note

This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is also supplied separately at an accompanying website. Topics and features: Introduces the fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning Discusses feed-forward neural networks, and explores the modifications to these which can be applied to any neural network Examines convolutional neural networks, and the recurrent connections to a feed-forward neural network Describes the notion of distributed representations, the concept of the autoencoder, and the ideas behind language processing with deep learning Presents a brief history of artificial intelligence and neural networks, and reviews interesting open research problems in deep learning and connectionism This clearly written and lively primer on deep learning is essential reading for graduate and advanced undergraduate students of computer science, cognitive science and mathematics, as well as fields such as linguistics, logic, philosophy, and psychology. Dr. Sandro Skansi is an Assistant Professor of Logic at the University of Zagreb and Lecturer in Data Science at University College Algebra, Zagreb, Croatia.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix. 9783319730042

International Standard Book Number

9783319730035

Artificial intelligence-- Mathematics.

Machine learning.

Neural networks (Computer science)

Coding theory & cryptology.

Coding theory.

Computer science.

Computers-- Computer Graphics.

Computers-- Computer Vision & Pattern Recognition.

Computers-- Database Management-- Data Mining.

Computers-- Information Theory.

Data mining.

Data mining.

Image processing.

Image processing.

Mathematical modelling.

Mathematics-- Applied.

Neural networks (Computer science)

Pattern perception.

Pattern recognition.

COM021030

UNF

UYQE

Number

Edition

Class number

Skansi, Sandro

Date of Transaction

20201221083243.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

270410

Y