Comparative corporate governance / (Record no. 22934)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03052cam a2200241 i 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781788975322 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1788975324 |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | English |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 346.0664 |
| Item number | COM |
| 245 00 - TITLE STATEMENT | |
| Title | Comparative corporate governance / |
| Statement of responsibility, etc | edited by Afra Afsharipour, Martin Gelter. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Cambridge, Massachusetts, |
| Name of publisher | The MIT Press, |
| Year of publication | 2017 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xx, 518 pages ; |
| Dimensions | 25 cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc | Includes bibliographical references and index. |
| 505 00 - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Introduction<br/>I. Applied math and machine learning basics. Linear algebra<br/>Probability and information theory<br/>Numerical computation<br/>Machine learning basics<br/>II. Deep networks : modern practices. Deep feedforward networks<br/>Regularization for deep learning<br/>Optimization for training deep models<br/>Convolutional networks<br/>Sequence modeling : recurrent and recursive nets<br/>Practical methodology<br/>Applications<br/>III. Deep learning research. Linear factor models<br/>Autoencoders<br/>Representation learning<br/>Structured probabilistic models for deep learning<br/>Monte Carlo methods<br/>Confronting the partition function<br/>Approximate inference<br/>Deep generative models |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Subject | Corporate governance |
| Form subdivision | Cross-cultural studies. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Subject | Corporation law. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Subject | Corporate governance. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Subject | Corporation law. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Author 2/ Editor | Afsharipour, Afra, |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Author 2/ Editor | Gelter, Martin, |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Books |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Use restrictions | Not for loan | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Bill Date | Full call number | Accession Number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Restricted Access | Institute of Public Enterprise, Library | Institute of Public Enterprise, Library | S Campus | 03/27/2024 | Atlantic Publishers | 26681.52 | 04/03/2024 | 346.0664 COM | 48385 | 03/27/2024 | Books |
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