Overview

D l rn ng has m rg d n th last f w r a r m r t hn l g for building intelligent t m th t l rn fr m d t . D n ur l networks, r g n ll r ughl inspired by h w the hum n br n l rn , are trained with large amounts f data t solve m l x tasks w th un r d nt d accuracy. W th n ur fr m w rk making this t hn l g w d l available, t b m ng a mu t-kn w for anybody involved with b g data and machine l rn ng.T n rFl w urr ntl the l d ng open source ftw r f r d l rn ng, used b a r dl gr w ng number f r t t n r w rk ng n m ut r v n, n tur l l ngu g processing (NLP), h r gn t n, nd general predictive n l t .Fr m large corporations t budd ng startups, engineers nd data scientists r ll t ng huge m unt f d t nd u ng m h n l rn ng lg r thm t n w r complex u t n nd build nt ll g nt t m . Wh r v r n l k in th l nd , th l of lg r thm associated w th d l rn ng h v r ntl seen gr t success, ft n l v ng tr d t n l m th d in the du t. D l rn ng u d t d to und r t nd the content f m g , n tur l l ngu g , nd speech, n t m r ng ng fr m m b l t ut n m u v h l . Developments n th field r t k ng l t breakneck d, with d l rn ng being xt nd d t other d m n and types f d t , l k m l x chemical nd genetic tru tur f r drug discovery nd h gh- dimensional m d l r rd n public h lth r .D l rn ng m th d -wh h l g b the n m f d neural n tw rk -w r originally roughly n r d b th hum n brain's v t network f interconnected n ur n . In deep l rn ng, w feed m ll n of d t instances nt a n tw rk f neurons, t h ng th m t recognize tt rn fr m raw inputs. The d n ur l networks t k r w inputs ( u h x l v lu n n image) nd transform them nt u ful r r nt t n , xtr t ng h gh r-l v l f tur (such shapes nd dg n images) th t capture complex n t b mb n ng smaller nd m ll r of information t lv challenging t k such as m g l f t n. Th networks ut m t ll l rn to bu ld b tr t representations b adapting and rr t ng themselves, fitting tt rn observed n th d t . The b l t t ut m t ll n tru t d t r r nt t n a key dv nt g f d neural n t v r conventional m h n l rn ng, which typically requires d m n expertise nd m nu l f tur engineering b f r any l rn ng can ur.

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