Statements (150)
Predicate | Object |
---|---|
gptkbp:instance_of |
gptkb:book
gptkb:machine_learning |
gptkbp:author |
gptkb:Yoshua_Bengio
gptkb:Aaron_Courville gptkb:Ian_Goodfellow |
gptkbp:available_formats |
gptkb:e_Book
Hardcover Paperback |
gptkbp:awards |
None listed
|
gptkbp:challenges |
gptkb:security
Overfitting Interpretability Computational Cost |
gptkbp:cover_art |
URL_to_cover_image
|
gptkbp:developed_by |
gptkb:Yoshua_Bengio
gptkb:Geoffrey_R._Hinton gptkb:Yann_Le_Cun |
gptkbp:field |
gptkb:Artificial_Intelligence
gptkb:neural_networks gptkb:machine_learning |
gptkbp:first_edition |
First
|
gptkbp:has_applications_in |
gptkb:Autonomous_Vehicles
gptkb:Natural_Language_Processing gptkb:speeches Image Recognition Recommender Systems |
gptkbp:has_method |
gptkb:Generative_Adversarial_Networks
gptkb:Deep_Belief_Networks gptkb:neural_networks gptkb:Recurrent_Neural_Networks gptkb:Transformer_Models |
https://www.w3.org/2000/01/rdf-schema#label |
Deep Learning
|
gptkbp:impact |
Influential in AI research
|
gptkbp:is_adopted_by |
Government Agencies
Research Institutions Startups Tech Companies |
gptkbp:is_based_on |
gptkb:neural_networks
|
gptkbp:is_characterized_by |
Feature Learning
High Computational Power Large Datasets Multi-layered Architecture |
gptkbp:is_cited_in |
Highly cited in academic papers
|
gptkbp:is_evaluated_by |
Accuracy
F1 Score Precision Recall Loss Function |
gptkbp:is_influenced_by |
Backpropagation
Regularization Techniques Gradient Descent |
gptkbp:is_popular_in |
gptkb:Computer_Vision
gptkb:Natural_Language_Processing gptkb:Artificial_Intelligence gptkb:Data_Science |
gptkbp:is_supported_by |
gptkb:Tensor_Flow
gptkb:Keras gptkb:Caffe gptkb:MXNet gptkb:Py_Torch |
gptkbp:is_trained_in |
gptkb:machine_learning
Supervised Learning Unsupervised Learning |
gptkbp:is_used_in |
gptkb:robotics
gptkb:Gaming Finance Healthcare |
gptkbp:isbn |
978-0262035613
|
gptkbp:language |
English
|
gptkbp:notable_feature |
gptkb:Generative_Adversarial_Networks
gptkb:neural_networks gptkb:stage_adaptation gptkb:Batch_Normalization gptkb:machine_learning gptkb:Recurrent_Neural_Networks gptkb:Dropout gptkb:Neural_Architecture_Search Autoencoders Backpropagation Regularization Techniques Optimization Algorithms Attention Mechanisms |
gptkbp:page_count |
800
|
gptkbp:published_year |
gptkb:2016
|
gptkbp:publisher |
gptkb:MIT_Press
|
gptkbp:related_works |
gptkb:Hands-On_Machine_Learning_with_Scikit-Learn,_Keras,_and_Tensor_Flow
gptkb:Deep_Reinforcement_Learning gptkb:Pattern_Recognition_and_Machine_Learning Deep Learning for Natural Language Processing Deep Learning for Anomaly Detection Deep Learning for Art Generation Deep Learning for Autonomous Vehicles Deep Learning for Climate Science Deep Learning for Computer Vision Deep Learning for Cybersecurity Deep Learning for Drug Discovery Deep Learning for Education Deep Learning for Energy Management Deep Learning for Finance Deep Learning for Fraud Detection Deep Learning for Gaming Deep Learning for Healthcare Deep Learning for Image Generation Deep Learning for Internet of Things (Io T) Deep Learning for Marketing Deep Learning for Music Generation Deep Learning for Network Security Deep Learning for Robotics Deep Learning for Signal Processing Deep Learning for Smart Cities Deep Learning for Social Media Analysis Deep Learning for Speech Recognition Deep Learning for Sports Analytics Deep Learning for Supply Chain Management Deep Learning for Telecommunications Deep Learning for Text Generation Deep Learning for Time Series Analysis Deep Learning for Video Analysis Neural Networks for Pattern Recognition Deep Reinforcement Learning Hands-On |
gptkbp:requires |
Advanced Algorithms
GPU Acceleration Large Amounts of Data |
gptkbp:reviews |
Highly regarded in the field
|
gptkbp:subject |
gptkb:Artificial_Intelligence
gptkb:neural_networks gptkb:machine_learning |
gptkbp:table_of_contents |
gptkb:Deep_Learning
Introduction Linear Algebra Conclusion Numerical Computation Applications Generative Models Convolutional Networks Machine Learning Basics Probability and Information Theory Deep Networks Sequence Modeling |
gptkbp:translated_into |
Multiple languages available
|
gptkbp:website |
http://www.deeplearningbook.org
|
gptkbp:bfsParent |
gptkb:Oak_Ridge_National_Laboratory
gptkb:Yoshua_Bengio gptkb:Andrew_Ng gptkb:Ian_Goodfellow gptkb:machine_learning gptkb:Artificial_Neural_Networks gptkb:Geoffrey_R._Hinton gptkb:Yann_Le_Cun |
gptkbp:bfsLayer |
3
|