LEADER 00909nam a2200241 i 4500 001 991000200359707536 008 040102s2000 it 000 0 ita d 020 $a8835098815 035 $ab12583704-39ule_inst 040 $aDip.to Scienze pedagogiche$bita 082 0 $a371.102 100 1 $aCalidoni, Paolo$0481604 245 10$aDidattica come sapere professionale :$bmateriali e appunti tra algoritmi e narrazioni /$cPaolo Calidoni 260 $aBrescia :$bLa Scuola,$cc2000 300 $a185 p. ;$c22 cm 440 0$aElementi di scienze dell'educazione 650 4$aDidattica 907 $a.b12583704$b21-09-06$c02-01-04 912 $a991000200359707536 945 $aLE022 371 CAL04.01$g1$i2022000107013$lle022$op$pE16.50$q-$rl$s- $t0$u2$v1$w2$x0$y.i13053322$z12-01-04 996 $aDidattica come sapere professionale$9252747 997 $aUNISALENTO 998 $ale022$b02-01-04$cm$d- $e-$fita$git $h0$i0 LEADER 02682nam 2200505 450 001 9910807841703321 005 20230803205032.0 010 $a1-4804-7700-1 035 $a(CKB)3710000000233852 035 $a(EBL)1799439 035 $a(SSID)ssj0001419466 035 $a(PQKBManifestationID)11897383 035 $a(PQKBTitleCode)TC0001419466 035 $a(PQKBWorkID)11396552 035 $a(PQKB)11487945 035 $a(MiAaPQ)EBC1799439 035 $a(Au-PeEL)EBL1799439 035 $a(CaONFJC)MIL594548 035 $a(OCoLC)892241663 035 $a(EXLCZ)993710000000233852 100 $a20181228h20141815 uy 1 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aEmma /$fJane Austen 210 1$aNew York, New York :$cOpen Road Media Integrated Media,$d2014. 210 4$dİ1815 215 $a1 online resource (822 p.) 300 $aDescription based upon print version of record. 327 $aCover; Title Page; Contents; VOLUME I; CHAPTER I; CHAPTER II; CHAPTER III; CHAPTER IV; CHAPTER V; CHAPTER VI; CHAPTER VII; CHAPTER VIII; CHAPTER IX; CHAPTER X; CHAPTER XI; CHAPTER XII; CHAPTER XIII; CHAPTER XIV; CHAPTER XV; CHAPTER XVI; CHAPTER XVII; CHAPTER XVIII; VOLUME II; CHAPTER I; CHAPTER II; CHAPTER III; CHAPTER IV; CHAPTER V; CHAPTER VI; CHAPTER VII; CHAPTER VIII; CHAPTER IX; CHAPTER X; CHAPTER XI; CHAPTER XII; CHAPTER XIII; CHAPTER XIV; CHAPTER XV; CHAPTER XVI; CHAPTER XVII; CHAPTER XVIII; VOLUME III; CHAPTER I; CHAPTER II; CHAPTER III; CHAPTER IV; CHAPTER V; CHAPTER VI; CHAPTER VII 327 $aCHAPTER VIIICHAPTER IX; CHAPTER X; CHAPTER XI; CHAPTER XII; CHAPTER XIII; CHAPTER XIV; CHAPTER XV; CHAPTER XVI; CHAPTER XVII; CHAPTER XVIII; CHAPTER XIX; Copyright 330 $aThe timeless romance starring one of Jane Austen's most unforgettable charactersEmma Woodhouse is a privileged young woman whose greatest pleasure in life lies in matchmaking for anyone but herself. Written, by Austen's own admission, as "a heroine whom no one but myself will much like," Emma's charm and wit exist in constant tension with her capacity for selfishness and vanity. Despite her intelligence, Emma stumbles from one catastrophe to the next-from a misguided attempt at securing a husband for her friend Harriet Smith to her disastrous meddling in the affairs of new arrivals Frank Churc 606 $aYoung women$vFiction 615 0$aYoung women 676 $a813.6 700 $aAusten$b Jane$f1775-1817,$0131233 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910807841703321 996 $aEmma$913191 997 $aUNINA LEADER 03554nam 22005775 450 001 9910483998803321 005 20251113193329.0 010 $a981-329-990-8 024 7 $a10.1007/978-981-32-9990-0 035 $a(CKB)4100000009837050 035 $a(MiAaPQ)EBC5976183 035 $a(DE-He213)978-981-32-9990-0 035 $a(PPN)243768206 035 $a(EXLCZ)994100000009837050 100 $a20191111d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEvolutionary Machine Learning Techniques $eAlgorithms and Applications /$fedited by Seyedali Mirjalili, Hossam Faris, Ibrahim Aljarah 205 $a1st ed. 2020. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2020. 215 $a1 online resource (287 pages) 225 1 $aAlgorithms for Intelligent Systems,$x2524-7573 311 08$a981-329-989-4 330 $aThis book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields. 410 0$aAlgorithms for Intelligent Systems,$x2524-7573 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aNeural networks (Computer science) 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aMathematical Models of Cognitive Processes and Neural Networks 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aNeural networks (Computer science). 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 676 $a006.31 702 $aMirjalili$b Seyedali$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aFaris$b Hossam$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAljarah$b Ibrahim$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483998803321 996 $aEvolutionary Machine Learning Techniques$91933714 997 $aUNINA