LEADER 01304nam a2200277 a 4500 001 991003438769707536 005 20250310125718.0 008 220620s2015 it 001 | 020 $a9788891728975 035 $ab14333685-39ule_inst 040 $aBibl. Dip.le Aggr. Scienze Giuridiche - Sez. Studi Giuridici$bita 082 0 $a711.43 100 1 $aLongo, Antonino$0104999 245 10$aCittą metropolitane e pianificazione di area vasta :$bprospettive di governo territoriale per la gestione delle metamorfosi urbane /$cAntonio Longo, Linda Cicirello. 260 $aMilano :$bAngeli,$c2015 300 $a206 p. :$bill. ;$c23 cm 490 0 $aUrbanistica 650 04$aCittą metropolitane$xPianificazione urbanistica 700 1 $aCicirello, Linda$eauthor$4http://id.loc.gov/vocabulary/relators/aut$0426118 907 $a.b14333685$b20-12-19$c03-01-18 912 $a991003438769707536 945 $aLE027 711.43 LON01.01$g1$i2027000294718$lle027$op$pE27.00$q-$rl$s-$t0$u0$v0$w0$x0$y.i15827276$z03-01-18 945 $aLE025 ECO 711 LON01.01$g1$i2025000285811$lle025$nProf. De Rubertis$o-$pE27.00$q-$rl$s-$t0$u1$v8$w1$x0$y.i15911652$z20-12-19 996 $aCittą metropolitane e pianificazione di area vasta$91748464 997 $aUNISALENTO 998 $ale027$ale025$b- -$cm$da$e-$fita$git$h0$i0 LEADER 01907nam a2200313 i 4500 001 991003577709707536 005 20251106134917.0 008 180911s2016 maua b 001 0 eng d 020 $a9780262035613 035 $ab14354706-39ule_inst 040 $aBibl. Dip.le Aggr. Ingegneria Innovazione - Sez. Ingegneria Innovazione$beng 082 00$a006.31$223 084 $aAMS 68-XX 100 1 $aGoodfellow, Ian$0752902 245 10$aDeep learning /$cIan Goodfellow, Yoshua Bengio and Aaron Courville 264 1$aCambridge, Massachusetts :$bThe MIT Press,$cc2016 300 $axxii, 775 p. :$bill. (some color) ;$c24 cm 490 0 $aAdaptive computation and machine learning 504 $aIncludes bibliographical references and index 505 0 $aApplied math and machine learning basics. Linear algebra -- Probability and information theory -- Numerical computation -- Machine learning basics -- Deep networks: modern practices. Deep feedforward networks -- Regularization for deep learning -- Optimization for training deep models -- Convolutional networks -- Sequence modeling: recurrent and recursive nets -- Practical methodology -- Applications -- Deep learning research. Linear factor models -- Autoencoders -- Representation learning -- Structured probabilistic models for deep learning -- Monte Carlo methods -- Confronting the partition function -- Approximate inference -- Deep generative models. 650 0$aMachine learning 700 1 $aBengio, Yoshua$eauthor$4http://id.loc.gov/vocabulary/relators/aut$0752903 700 1 $aCourville, Aaron 907 $a.b14354706$b04-12-18$c29-11-18 912 $a991003577709707536 945 $aLE026 006.31 GOO 01.01 2016$g1$i2026000073033$lle026$nProf. Ricci / Biblioteca$op$pE82.50$q-$rl$s-$t4$u5$v0$w5$x0$y.i15870753$z04-12-18 996 $aDeep learning$91749342 997 $aUNISALENTO 998 $ale026$b11-09-18$cm$da$feng$gmau$h0$i0