Goodfellow, Ian creator autor. aut Bengio, Yoshua Courville, Aaron text mau 2016 monographic spa eng

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xvii, 775 páginas (algunas a color) : ilustraciones ; 24 centímetros . Una introducción a una amplia gama de temas en el aprendizaje profundo, que cubre antecedentes matemáticos y conceptuales, técnicas de aprendizaje profundo utilizadas en la industria y perspectivas de investigación. Applied Math and machine learning basics -- Linear algebra -- Probability and information theory -- Numerical computation -- Mchine learning basics -- Deep networks: modern practices -- Deep feedforward networks -- Regularization for deep lerning -- Optimization for training deep models -- Convolutional networks -- Sequence modeling: recurrent and recursive nets -- Practical methodology -- Applications -- Deep learning research: Linear factors models -- Autoencoders -- Representation learning -- Structured probabilistic models for deep learning -- Mote Carlo methods -- Confronting the partition Function -- Appoximate Inference -- Deep Generative models . Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Incluye bibliografía e índice. Deep learning Algebra lineal Machine learning Redes de computadores 006.3 G651d 9780262035613 CO-ViULL 220601 20251030135754.0 spa