TY  - BOOK
AU  - Buduma,Nithin
AU  - Buduma,Nikhil
AU  - Papa Joe
AU  - Locascio,Nicholas
TI  - Fundamentals of deep learning: designing next-generation machine intelligence algorithms 
SN  - 9781492082187
U1  - 006.31 23
PY  - 2022///]
CY  - Sebastopol, CA
PB  - O'Reilly Media, Inc.
KW  - INTELIGENCIA ARTIFICIAL
KW  - APRENDIZAJE AUTOMATICO
KW  - Neural networks (Computer science)
KW  - REDES NEURONALES (ciencia de la computación)
N1  - Previous edition: published as by Nikhil Buduma with contributions by Nicholas Locascio. 2017; Fundamentals of linear algebra for deep learning -- Fundamentals of probability -- The neural network -- Training feed-forward neural networks -- Implementing neural networks in PyTorch -- Beyond gradient descent -- Convolutional neural networks -- Embedding and representation learning -- Models for sequence analysis -- Generative models -- Methods in interpretability -- Memory augmented neural networks -- Deep reinforcement learning
N2  - We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics. The updated second edition of this book describes the intuition behind these innovations without jargon or complexity
UR  - https://bibliotecadigital.usm.cl/info/01609652
ER  -