01560nam--2200409---450-99000289026020331620070704085234.092-894-7526-9000289026USA01000289026(ALEPH)000289026USA0100028902620070328d2005----km-y0itaa50------baengLUa---z---001yyNew business opportunities for EU companies in Pakistanan investor´s guidebookAsia Invest, EuropeAid, Co-operation Office[consultants and authors of this report, Philippe Guitard, Shahid Ahmed Khan, Derk Bienenwith the assistance of the European Union under the Asia-Invest programme]LuxembourgOffice for official publications of the European communities2005XXIII-162 p.30 cmPakistanCondizioni economiche e socialiSec. 20.InvestimentiPakistan330.954703.01EconomiaGUITARD,PhilippeKHAN,Shahid AhmedBIENEN,DerkCOMMISSIONE EUROPEA :Ufficio di cooperazione EuropeAid596426ITsalbcISBD990002890260203316CDE 03.01 (I)CDECDE 03.0100149180BKCDEMARIAS9020070328USA011238MARIAS9020070330USA011145MARIAS9020070704USA010852New business opportunities for EU companies in Pakistan989732UNISA01403nam 2200337 450 99657531190331620231213213428.01-5044-9358-3(CKB)4100000012904014(NjHacI)994100000012904014(EXLCZ)99410000001290401420231213d2023 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrier2841-2022 - IEEE Recommended Practice for Framework and Process for Deep Learning Evaluation /Institute of Electrical and Electronics EngineersNew York :IEEE,2023.1 online resource (32 pages)Includes bibliographical references.The recommendations on evaluating and improving algorithm reliability for shortening the development cycle of deep learning algorithms and improving the quality of software systems based on deep learning algorithms are defined in this document. An assessment index system and corresponding assessment process are specified in this document.AlgorithmsAlgorithms.518.1NjHacINjHaclBOOK9965753119033162841-2022 - IEEE Recommended Practice for Framework and Process for Deep Learning Evaluation3880992UNISA