Publication | Open Access
Book Review: Deep Learning
211
Citations
6
References
2016
Year
Artificial IntelligenceConvolutional Neural NetworkEngineeringMachine LearningNeural Networks (Machine Learning)Ai FoundationMany LayersAi Deep LearningSocial SciencesRepresentation LearningKnowledge Graph EmbeddingsData ScienceKnowledge RepresentationComputer ScienceNeural Networks (Computational Neuroscience)Knowledge GraphsDeep LearningIntuitive ProblemsDeep Neural NetworksGraph Neural NetworkExplainable Ai
This book offers a solution to more intuitive problems in these areas. These solutions allow computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined in terms of its relationship to simpler concepts. By gathering knowledge from experience, this approach avoids the need for human operators to specify formally all of the knowledge needed by the computer. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones. If the authors draw a graph to show how these concepts have been built on top of each other, the graph will be deep, with many layers. For this reason, the authors call this approach “AI Deep Learning.”
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