LEADER 00933nam--2200337---450 001 990000481800203316 005 20210430104251.0 010 $a88-425-1679-1 035 $a0048180 035 $aUSA010048180 035 $a(ALEPH)000048180USA01 035 $a0048180 100 $a20010530d1994----km-y0itay0103----ba 101 $aita 102 $aIT 105 $a||||||||001yy 200 1 $aStoria della violenza politica$fEzio Cecchini 210 $aMilano$cMursia$d1994 215 $a478 p.$d22 cm 225 2 $aStoria e documenti$v132 410 $12001$aStoria e documenti$v132 606 0 $aDelitti politici$xStoria 676 $a364.152409 700 1$aCECCHINI,$bEzio$0253975 801 0$aIT$bsalbc$gISBD 912 $a990000481800203316 951 $aX.3.B. 1120(III A COLL. 96/132)$b117341 L.M.$cIII A COLL. 959 $aBK 969 $aUMA 996 $aStoria della violenza politica$9888500 997 $aUNISA LEADER 03339nam 2200541 450 001 9910460215103321 005 20200520144314.0 010 $a92-4-069274-6 035 $a(CKB)3710000000245157 035 $a(EBL)1809075 035 $a(SSID)ssj0001337965 035 $a(PQKBManifestationID)12573153 035 $a(PQKBTitleCode)TC0001337965 035 $a(PQKBWorkID)11337349 035 $a(PQKB)10822649 035 $a(MiAaPQ)EBC1809075 035 $a(Au-PeEL)EBL1809075 035 $a(CaPaEBR)ebr10931323 035 $a(OCoLC)880358467 035 $a(EXLCZ)993710000000245157 100 $a20140922h20132013 uy| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 181 $csti$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aTrichiasis surgery for trachoma $eupdate of <> and <> 205 $aSecond Edition / Electronic version. 210 1$a[Albany, New York] :$cWorld Health Organization,$d[2013] 210 4$dİ2013 215 $a1 online resource (72 pages) $cillustrations 300 $a"Update of Trichiasis surgery for trachoma, the bilamellar tarsal rotation procedure and Final assessment of trichiasis surgeons." 311 $a92-4-154867-3 320 $aIncludes bibliographical references. 327 $aSection One: Introduction -- The Anatomy of the Eye and the Eyelid -- Trachoma and its Effect on the Eye -- History and Examination for Upper Eyelid Trichiasis -- Indications for Eyelid Surgery -- Fitness of Patient for Surgery -- Facilities and Surgical Materials -- Sterilization -- Preparation -- Injecting Local Anaesthetic -- Surgical Procedure -- Postoperative Care -- Results -- Section Two: For Trainers: Introduction -- Final Assessment of TT Surgeons -- Checklist 330 $aThe second edition of this manual combines and updates material contained in three previous manuals on bilamellar tarsal rotation procedure, Trabut procedure, and the final assessment of candidate trichiasis surgeons. This manual is designed to provide specific information for trachomatous trichiasis (TT) trainers who are training others to undertake surgery for entropion trachomatous trichiasis (TT). Other approaches are not addressed. The manual is divided into two parts. The first part covers specifics designed for training TT surgeon candidates, and serves as a resource document. The trainer can elect to have trainees read the material directly, use this manual as a guide for creating a training presentation, or use it in other ways to assist in the training. The manual contains both knowledge that should be imparted during training and a description of the skills that need to be developed and assessed during practice and surgery sessions. The second part is designed ONLY for the trainers of the surgeon trainees and covers selection and final assessment of the trainees. -- Publisher 606 $aEye$xSurgery 608 $aElectronic books. 615 0$aEye$xSurgery. 676 $a617.772 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910460215103321 996 $aTrichiasis surgery for trachoma$92014935 997 $aUNINA LEADER 03366nam 2200445 450 001 9910555068903321 005 20200629190457.0 010 $a1-119-60291-2 010 $a1-119-60292-0 010 $a1-119-60290-4 035 $a(CKB)4100000010327523 035 $a(MiAaPQ)EBC6109530 035 $a(PPN)272715220 035 $a(CaSebORM)9781119602873 035 $a(OCoLC)1143273891 035 $a(EXLCZ)994100000010327523 100 $a20200408d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine learning for iOS developers /$fAbhishek Mishra 205 $a1st edition 210 1$aHoboken, New Jersey :$cWiley,$d[2020] 210 4$dİ2020 215 $a1 online resource (352 pages) 311 $a1-119-60287-4 330 $aHarness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner! Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple?s ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications. Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book?s clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models?both pre-trained and user-built?with Apple?s CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers: Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming Develop skills in data acquisition and modeling, classification, and regression. Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS) Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps. 606 $aMachine learning 615 0$aMachine learning. 676 $a006.31 700 $aMishra$b Abhishek$0887481 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910555068903321 996 $aMachine learning for iOS developers$92816606 997 $aUNINA