Deep Learning (book)
E4032
Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
All labels observed (5)
| Label | Occurrences |
|---|---|
| Deep Learning (book) canonical | 3 |
| Deep Learning | 2 |
| Deep Learning (Goodfellow, Bengio, Courville) | 1 |
| Deep Learning (MIT Press, 2016) | 1 |
| Part II: Modern Practical Deep Networks | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T55605 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deep Learning (book) Context triple: [Yoshua Bengio, coAuthorOf, Deep Learning (book)]
-
A.
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence is a leading peer-reviewed journal that publishes cutting-edge research in computer vision, pattern recognition, and machine learning.
-
B.
Geoffrey Hinton
Geoffrey Hinton is a pioneering computer scientist widely regarded as one of the founding figures of deep learning and modern artificial intelligence.
-
C.
Yoshua Bengio
Yoshua Bengio is a Canadian computer scientist and deep learning pioneer whose work on neural networks and representation learning has been foundational to modern artificial intelligence.
-
D.
Literary Machines
Literary Machines is a seminal book by Theodor Nelson that outlines his visionary concepts for hypertext, non-linear writing, and the structure of digital information systems.
-
E.
Wholly New Forms of Encyclopedias
"Wholly New Forms of Encyclopedias" is a section of Vannevar Bush’s essay "As We May Think" that envisions future, highly interconnected and dynamically organized knowledge systems beyond traditional printed encyclopedias.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Deep Learning (book) Target entity description: Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
-
A.
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence is a leading peer-reviewed journal that publishes cutting-edge research in computer vision, pattern recognition, and machine learning.
-
B.
Geoffrey Hinton
Geoffrey Hinton is a pioneering computer scientist widely regarded as one of the founding figures of deep learning and modern artificial intelligence.
-
C.
Yoshua Bengio
Yoshua Bengio is a Canadian computer scientist and deep learning pioneer whose work on neural networks and representation learning has been foundational to modern artificial intelligence.
-
D.
Literary Machines
Literary Machines is a seminal book by Theodor Nelson that outlines his visionary concepts for hypertext, non-linear writing, and the structure of digital information systems.
-
E.
Wholly New Forms of Encyclopedias
"Wholly New Forms of Encyclopedias" is a section of Vannevar Bush’s essay "As We May Think" that envisions future, highly interconnected and dynamically organized knowledge systems beyond traditional printed encyclopedias.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
computer science book
ⓘ
machine learning book ⓘ non-fiction book ⓘ textbook ⓘ |
| author |
Aaron Courville
ⓘ
Ian Goodfellow ⓘ Yoshua Bengio ⓘ |
| countryOfPublication |
United States of America
ⓘ
surface form:
United States
|
| coversAlgorithm |
backpropagation
ⓘ
stochastic gradient descent ⓘ |
| coversConcept |
generalization in machine learning
ⓘ
overfitting ⓘ underfitting ⓘ |
| field |
artificial intelligence
ⓘ
deep learning ⓘ machine learning ⓘ |
| hasPart |
Part I: Applied Math and Machine Learning Basics
ⓘ
Deep Learning (book) self-linksurface differs ⓘ
surface form:
Part II: Modern Practical Deep Networks
Part III: Deep Learning Research ⓘ |
| isbn10 | 0262035618 ⓘ |
| isbn13 | 9780262035613 ⓘ |
| language | English ⓘ |
| mediaType |
ebook
ⓘ
print ⓘ |
| notableFor |
being a widely used deep learning textbook
ⓘ
systematic introduction to modern deep neural networks ⓘ |
| pageCount | 775 ⓘ |
| publicationYear | 2016 ⓘ |
| publisher | MIT Press ⓘ |
| subject |
applications of deep learning
ⓘ
convolutional networks ⓘ deep feedforward networks ⓘ deep generative models ⓘ linear algebra ⓘ neural networks ⓘ numerical computation ⓘ optimization ⓘ optimization for training deep models ⓘ practical methodology ⓘ probability and information theory ⓘ regularization ⓘ representation learning ⓘ sequence modeling ⓘ |
| targetAudience |
graduate students
ⓘ
practitioners ⓘ researchers ⓘ |
| title |
Deep Learning (book)
self-linksurface differs
ⓘ
surface form:
Deep Learning
|
| usesNotation | mathematical notation ⓘ |
| website | http://www.deeplearningbook.org ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Deep Learning (book) Description of subject: Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
Referenced by (8)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Deep Learning
this entity surface form:
Part II: Modern Practical Deep Networks
this entity surface form:
Deep Learning
subject surface form:
Yoshua Bengio
this entity surface form:
Deep Learning (MIT Press, 2016)
this entity surface form:
Deep Learning (Goodfellow, Bengio, Courville)