Th???i c, t t c c???c model d o???n (predictive models) u tr???ng c??? v n, nh ng l???m c???ch n???o ch???ng ta c??? th x???y d ng c???c model m t c???ch ???ng tin c y h n? ???y ch???nh l??? c???u h i t???i th ng c h i b i c???c nh??? khoa h c d li u nh ng m c kinh nghi m kh???c nhau. C???u h i c??? v n gi n, nh ng ng th i c ng r t th???ch th c b i v??? c??? r t nhi u lu ng quan i m v??? m i quan t???m kh???c nhau t nh ng ng i li???n quan. Nh ng ng i x???y d ng model th ng t p trung v???o vi ...
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Th???i c, t t c c???c model d o???n (predictive models) u tr???ng c??? v n, nh ng l???m c???ch n???o ch???ng ta c??? th x???y d ng c???c model m t c???ch ???ng tin c y h n? ???y ch???nh l??? c???u h i t???i th ng c h i b i c???c nh??? khoa h c d li u nh ng m c kinh nghi m kh???c nhau. C???u h i c??? v n gi n, nh ng ng th i c ng r t th???ch th c b i v??? c??? r t nhi u lu ng quan i m v??? m i quan t???m kh???c nhau t nh ng ng i li???n quan. Nh ng ng i x???y d ng model th ng t p trung v???o vi c hu n luy n model (training model) m t c???ch t ng, ki m so???t hi u n ng, debug v??? nh ng ho t ng duy tr??? c h th ng t d li u n t i u hi u n ng ph n c ng v??? c i ti n model (MLOps). Ng i s d ng model ph n nhi u th ng h ng th??? h n v i nh ng c???u h i v t ???u m??? model cho ra k t qu d o???n nh v y (explainability) ho c nh ng ???i h i nh t nh hi u c b???n trong model ho t ng nh th n???o (transparency) v??? m c "ph???ng th " (security) c a m??? h???nh tr c nh ng t n c???ng, v??? d nh t d li u k???m ch t l ng. V ph???a x??? h i, nh ng m i quan t???m th ng l??? model c??? c???ng b ng hay thi???n v (fairness hay bias), v??? d m??? h???nh c??? u ti???n cho m t nh???m ng i nh trong x??? h i, ho c thi???n v v gi i t???nh kh???ng; hay k t qu d o???n t model c??? ph??? h p chu n m c o c hay kh???ng (ethics). Quy n s???ch n???y t ng h???a t t c c???c g???c nh???n tr???n. B n c s t???m th y nh ng k thu t machine learning ch n l c v??? c nh ng c???ch hi u tr c quan ng n g n. C???c k thu t u c g n li n v i c???c o n code trong ng???n ng R. B n c s c???ng hai nh???n v t B???ta v??? B???t i d o v???o khu v n, kh???ng ph i c a k??? hoa d th o, m??? l??? c a c???c model ML th??? v . Trong khu v n c??? ng n ???n c th p l???n b i nh ng g???c nh???n th u ???o v model t kinh nghi m th c t . Cu c b???n lu n gi a B???ta v??? B???t c ng ch???nh l??? nh ng g??? di n ra trong th c t m??? c???c nh??? khoa h c d li u th ng g p, c??? n???n th m t model kh???c kh???ng, ho c c??? n???n th m t k thu t kh???c khai ph??? d li u, ho c m t t p d li u kh???c ch ng? --- v??? ti t c???u h i nh l???m c???ch n???o so s???nh gi a nh ng model ho c l???m th n???o ki m tra hi u n ng. Qu??? tr???nh ph???t tri n model ???i h i s c n th n v??? tr???ch nhi m, nh ng r t th??? v . Th???ng th ng, nhi u quy n s???ch ch ch??? t???m v???o m t ki n th c m??? qu???n m t i ni m vui v??? s th??? v . Nh ng, hi v ng quy n s???ch n???y, ch???ng ta s c??? c c hai.
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