I-Keras

Njengengcali kwiprogram yePython kunye ne-Keras Deep Learning framework, ndiyabuqonda ubunzima obubandakanyekayo ekulayisheni imodeli, ngakumbi xa imodeli yakho isebenzisa umsebenzi wokulahlekelwa kwesiko. Eli nqaku likukhokela ngendlela yokoyisa le mingeni kwaye ulayishe ngempumelelo imodeli yakho yeKeras ngomsebenzi welahleko yesiko.

I-Keras, i-API yothungelwano olukwinqanaba eliphezulu le-neural, isebenziseka lula kwaye imodyuli, ekwaziyo ukubaleka ngaphezulu kweTensorFlow okanye iTheano. Iyaziwa ngobulula bayo kunye nokulula ukuyisebenzisa. Nangona kunjalo, ngaphandle kokulula kwayo, ukuqonda imisebenzi ethile efana nokulayisha imodeli ngomsebenzi welahleko yesiko kunokuba nzima kakhulu.

Funda Okuninzi

Uluhlu lwamagama kulo mxholo lubhekisa kulwakhiwo lombutho oludla ngokusetyenziswa kwiikhowudi, ukwenza iikhowudi zifundeke ngakumbi, zicwangciswe kwaye ziqondwe lula. Uluhlu lwamagama lukwaphucula impumelelo ekusebenzeni kwekhowudi ngenxa yolwakhiwo olucwangcisiweyo olucwangcisiweyo. Ukufumana ukuqonda okugcweleyo malunga nendlela amagama asebenza ngayo kwiPython, masingene kwingcambu yengxaki.

Funda Okuninzi

Ukwakha imodeli yenethiwekhi ye-neural ngummandla onomdla wokufunda koomatshini, ngakumbi kwiPython. Inika umda obanzi wokuhlalutya, uqikelelo, kunye neenkqubo zokuthatha izigqibo ezizenzekelayo. Phambi kokuba singene kwi-nitty-gritty yokwakha iyelenqe lothungelwano lwe-neural, kubalulekile ukuqonda ukuba yintoni inethiwekhi ye-neural. Ngokwesiseko yinkqubo ye-algorithms enxulumanisa ubume bobuchopho bomntu, ngaloo ndlela idala inethiwekhi ye-neural eyenziweyo ethi, ngenkqubo yohlalutyo itolike idatha yeemvakalelo, ithathela ingqalelo iinuances 'ezingabonakaliyo' ngedatha ekrwada, njengoko yenzayo ingqondo yethu.

Funda Okuninzi

Ngokuqinisekileyo, masiqalise ngenqaku.

Iimodeli zokufunda nzulu ziye zaba ngumba obalulekileyo wetekhnoloji kweli xesha lanamhlanje, kwaye iindlela ezahlukeneyo zokusebenzisa iindlela ezifana noAdam Optimizer zidlala indima ebalulekileyo ekusebenzeni kwazo. I-Keras, ithala leencwadi lePython elinamandla nekulula ukulisebenzisa simahla ukuze liphuhlise kwaye livavanye iimodeli zokufunda ezinzulu, isonga amathala eencwadi asebenzayo okubala amanani eTheano kunye neTensorFlow.

Funda Okuninzi

I-Keras lithala leencwadi elinamandla nelisebenzayo lokwenza iimodeli zokufunda ngoomatshini, ngakumbi iimodeli zokufunda nzulu. Enye yeempawu zayo kukucwangcisa imodeli yethu kwidayagram ukuze kube lula ukuqonda kunye nokusombulula ingxaki. Ngamanye amaxesha ukuqhuba keras.utils.plot_model kunokuphosa iimpazamo ezibonisa iimfuno zesoftware engekhoyo, ngakumbi ipydot kunye negraphviz. Kulindeleke ukuba uzifake zombini. Nangona kunjalo, nasemva kokuba uzifakile, usenokufumana umyalezo ofanayo wempazamo. Oku kungenxa yeendlela kunye nezicwangciso zoqwalaselo ezingasetwanga kakuhle. Ngeli nqaku, siza kuhamba kwinkqubo yokusombulula lo mba uthile.

Funda Okuninzi

Ucinga ukuba ufuna inqaku lokuhamba kwePython kwi-NumPy Arrays, nali inqaku lakho:

Ngaphambi kokuba singene entloko kwiinkcukacha zomkhondo kwiPython, kubalulekile ukuba siqale siqonde ukuba ziyintoni na. Imitsi yimbono ekwiPython ephucula kakhulu uqhatha kunye nokuphathwa koluhlu, ngakumbi uluhlu lweNumPy.. Isinika amandla okulawula ngokufanelekileyo uluhlu ngaphandle kwesidingo sememori eyandisiweyo okanye iindleko zokubala. Ixabiso lomgama likhomba kumanyathelo athatyathwe yiPython xa unqumla kuluhlu. Ngoku makhe sihlolisise indlela esinokulisebenzisa ngayo eli nqaku likhethekileyo ukusombulula iingxaki.

Funda Okuninzi

Kwihlabathi lenkqubo yekhompyuter, ukudibana neempazamo yinto eqhelekileyo. Thatha, umzekelo, i KeyError: 'acc' in Python. Le mpazamo idla ngokuvela xa iqhosha elithile sizama ukufikelela kwisichazi-magama lingekho. Ngethamsanqa, iPython ibonelela ngesisombululo esicacileyo sokujongana nemiba enjalo kwaye ithintele ikhowudi yakho ekuweni. Oku kuquka ukusebenzisa iinkqubo zokuphatha, ukusebenzisa i get() umsebenzi, okanye ukujonga izitshixo phambi kokuba ufikelele kuzo. Ngendlela efanelekileyo, le mpazamo inokulawulwa ngobuchule.

Funda Okuninzi

I-Parametric Rectified Linear Units, okanye i-PReLU, izisa ukulungelelaniswa kwe-Keras convolution layers. Kanye njengoko ifashoni iqhelana nokutshintsha kweendlela, kunjalo nangeemodeli zakho ze-AI. Olu phawu luthatha umsebenzi odumileyo weRectified Linear Unit (ReLU) inyathelo eliya phambili ngokuvumela i-slope engalunganga ifundwe kwidatha yegalelo, kunokuba ihlale ilungisiwe. Ngokwezinto ezisebenzayo, oku kuthetha ukuba nge-PRELU, iimodeli zakho ze-AI zinokukhupha kwaye zifunde zombini iimpawu ezilungileyo nezingalunganga kwidatha yakho yegalelo, iphucula ukusebenza kunye nokusebenza kakuhle.

Funda Okuninzi