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1. |
Record Nr. |
UNISA996393231003316 |
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Autore |
Burrough Edward <1634-1662.> |
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Titolo |
A description of the state and condition of all mankinde upon the face of the whole earth [[electronic resource] ] : And a discovery unto all; shewing what man was in his creation before transgression, and what he is in transgression ... Also, the way of restoration, of salvation, redemption, and of life eternal, is here declared ... that all may come to the knowledge of the Creator, and to have fellowship with him again, from whom all the children of men are separated in the state of enmity, and are ignorant of him, and drove from his presence. This is to go abroad into all the earth, through the whole world ... that they ... may be restored again to serve, and worship, and glorifie the living God, who made heaven and earth, and all things therein / By ... Edward Burrough |
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Pubbl/distr/stampa |
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London, : printed for Giles Calvert, and are to be sold at his shop at the Black-spread-Eagle neer the west end of Pauls, [1657] |
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Descrizione fisica |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Publication date from Wing. |
Annotation on Thomason copy: "May 28 1657". |
Reproduction of the original in the British Library. |
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Sommario/riassunto |
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2. |
Record Nr. |
UNINA9911019224503321 |
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Autore |
Basha Niha Kamal |
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Titolo |
Deep Learning and Its Applications Using Python |
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Pubbl/distr/stampa |
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Newark : , : John Wiley & Sons, Incorporated, , 2024 |
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©2023 |
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ISBN |
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9781394167791 |
1394167792 |
9781394167784 |
1394167784 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (255 pages) |
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Altri autori (Persone) |
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Bhatia KhanSurbhi |
KumarAbhishek |
MashatArwa |
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Disciplina |
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Soggetti |
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Deep learning (Machine learning) |
Python (Computer program language) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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This book thoroughly explains deep learning models and how to use Python programming to implement them in applications such as NLP, face detection, face recognition, face analysis, and virtual assistance (chatbot, machine translation, etc.). It provides hands-on guidance in using Python for implementing deep learning application models. It also identifies future research directions for deep learning. |
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