UID:
kobvindex_GFZ865398267
Format:
xxii, 775 Seiten
,
Illustrationen, Diagramme
ISBN:
9780262035613
Series Statement:
Adaptive computation and machine learning
Content:
Applied math and machine learning basics. Linear algebra -- Probability and information theory -- Numerical computation -- Machine learning basics -- Deep networks: modern practices. Deep feedforward networks -- Regularization for deep learning -- Optimization for training deep models -- Convolutional networks -- Sequence modeling: recurrent and recursive nets -- Practical methodology -- Applications -- Deep learning research. Linear factor models -- Autoencoders -- Representation learning -- Structured probabilistic models for deep learning -- Monte Carlo methods -- Confronting the partition function -- Approximate inference -- Deep generative models
Note:
Literaturverzeichnis: Seite 711-766
,
Hier auch später erschienene, unveränderte Nachdrucke
,
Weitere Infos unter http://www.deeplearningbook.org/
Language:
English
