Introduction to Deep Learning / (Record no. 40807)

MARC details
000 -LEADER
fixed length control field 01994nam a22002777a 4500
003 - CONTROL NUMBER IDENTIFIER
control field CUTN
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20231207111801.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 231207b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789188364807
041 ## - LANGUAGE CODE
Language English
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Edition number 23
Classification number 006.31
Item number ADR
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Adrean, Kurt.
240 ## - UNIFORM TITLE
Uniform title <a href="Introduction to Deep Learning ">Introduction to Deep Learning </a>
245 ## - TITLE STATEMENT
Title Introduction to Deep Learning /
Statement of responsibility, etc Kurt Adrean.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Gotland :
Name of publisher, distributor, etc Lynas Publishing,
Date of publication, distribution, etc 2023.
300 ## - PHYSICAL DESCRIPTION
Extent 163 p. :
Other physical details ill. ;
Dimensions 23 cm.
505 ## - FORMATTED CONTENTS NOTE
Title 1. License<br/>2. Deep Learning Tutorials<br/>3. Getting started<br/>4. Classifying MNIST digits using Logistics Regression<br/>5. Multiplayer Perceptron<br/>6. Convolution Neural Networks (LeNet)<br/>7. Denoising Autoencoders (dA)<br/>8. Stacked Denoising Autoencoders (dA)<br/>9. Restricted Boltzman Machine (RBM)<br/>10. Deep Belief Networks<br/>11. Hybrid Monte-Carlo Sampling<br/>12. Recurrent Neural Networks with Word Embeddings<br/>13. LSTM Networks for Sentiment Analysis<br/>14. Modelling and Generating sequences of polyphonic music with RNN-RBM<br/>15. Miscellaneous<br/>Index
520 ## - SUMMARY, ETC.
Summary, etc The book guides you to deep learning through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning. The author, a long time artificial intelligence researchers specializing in natural -language processing, covers feed-forward neural nets, convolutional neural nets, word embeddings, recurrent neural nets, sequence-to-sequence learning, deep reinforcement learning, unsupervised models, and other fundamentals concepts and techniques. Students and practitioners learn the basic of deep learning by working through programs in Tensorflow, an open-source machine learning framework.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element LSTM
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Boltzman Machine
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Logistics Regression
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Perceptron
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Convolution Neural Networks (LeNet)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element MNIST
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Text Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Location Shelving location Date of Cataloging Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Non-fiction CUTN Central Library CUTN Central Library Generalia 07/12/2023   006.31 ADR 46856 07/12/2023 07/12/2023 Text Books

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