Hello, Habr! Waxaan dareenkaaga ku soo bandhigayaa tarjumaad maqaalka waxaa qoray kristincarter7519.
Inkasta oo ay u muuqato in ay dhawr maalmood ka hadhsan yihiin sannadka 2020, haddana maalmahan waxa ay sidoo kale muhiim u yihiin dhinaca horumarinta software-ka. Halkan maqaalkan, waxaan ku arki doonaa sida sanadka soo socda ee 2020 uu u bedeli doono nolosha kuwa horumariya software-ka.
Mustaqbalka horumarinta software waa halkan!
Horumarinta software-dhaqameedku waa horumarinta software iyada oo la qorayo koodka iyada oo la raacayo qaar ka mid ah xeerar go'an. Laakin horumarinta software-ka casriga ah waxa ay goob joog u noqotay isbedel ku yimid horumarka xagga garaadka macmalka ah, barashada mashiinka iyo barashada qoto dheer. Marka la isku daro saddexdan tignoolajiyada, horumariyayaashu waxay awood u yeelan doonaan inay abuuraan xalal software oo wax ka baranaya tilmaamaha oo ku dara sifooyin iyo qaabab dheeraad ah xogta loo baahan yahay si loo soo saaro natiijada la rabo.
Aan isku dayno kood
Muddo ka dib, nidaamyada horumarinta software ee shabakada neural waxay noqdeen kuwo aad u adag marka la eego isdhexgalka iyo sidoo kale heerarka shaqeynta iyo isdhexgalka. Horumariyayaashu, tusaale ahaan, waxay dhisi karaan shabakad neerfaha ah oo aad u fudud oo leh Python 3.6. Halkan waxaa ah barnaamij tusaale ah oo sameeya kala soocida binary ee leh 1s ama 0s.
Dabcan, waxaan ku bilaabi karnaa abuurista fasalka shabakada neerfaha:
soo deji NumPy sidii NP
X=np.array([[0,1,1,0],[0,1,1,1],[1,0,0,1]])
y=np.array([[0],[1],[1]])Codsiga shaqada sigmoid:
def sigmoid ():
return 1/(1 + np.exp(-x))
def derivatives_sigmoid ():
return x * (1-x)Tababar nooc leh miisaan hore iyo eex:
epoch=10000
lr=0.1
inputlayer_neurons = X.shape[1]
hiddenlayer_neurons = 3
output_neurons = 1
wh=np.random.uniform(size=(inputlayer_neurons,hiddenlayer_neurons))
bh=np.random.uniform(size=(1,hiddenlayer_neurons))
wout=np.random.uniform(size=(hiddenlayer_neurons,output_neurons))
bout=np.random.uniform(size=(1,output_neurons))Kuwa bilawga ah, haddii aad u baahan tahay caawimo ku saabsan shabakadaha neerfaha, waxaad ka raadin kartaa internetka boggaga internetka ee shirkadaha horumarinta software ama waxaad shaqaaleysiin kartaa horumarinta AI/ML si ay uga shaqeeyaan mashruucaaga.
Beddelka code iyadoo la isticmaalayo lakabka wax soo saarka neuron
hidden_layer_input1=np.dot(X,wh)
hidden_layer_input=hidden_layer_input1 + bh
hiddenlayer_activations = sigmoid(hidden_layer_input)
output_layer_input1=np.dot(hiddenlayer_activations,wout)
output_layer_input= output_layer_input1+ bout
output = sigmoid(output_layer_input)
Cilada xisaabinta ee lakabka koodka qarsoon
E = y-output
slope_output_layer = derivatives_sigmoid(output)
slope_hidden_layer = derivatives_sigmoid(hiddenlayer_activations)
d_output = E * slope_output_layer
Error_at_hidden_layer = d_output.dot(wout.T)
d_hiddenlayer = Error_at_hidden_layer * slope_hidden_layer
wout += hiddenlayer_activations.T.dot(d_output) *lr
bout += np.sum(d_output, axis=0,keepdims=True) *lr
wh += X.T.dot(d_hiddenlayer) *lr
bh += np.sum(d_hiddenlayer, axis=0,keepdims=True) *lrKa bax
print (output)
[[0.03391414]
[0.97065091]
[0.9895072 ]]Had iyo jeer waa mudan tahay in lala socdo luuqadaha barnaamijyada ugu dambeeyay iyo farsamooyinka codaynta, sidoo kale barnaamij-sameeyayaashu waa inay ka warqabaan aalado badan oo cusub oo ka caawiya ka dhigista barnaamijyadooda inay la xiriiraan isticmaaleyaasha cusub.
Sannadka 2020, horumariyayaashu waa inay ka fikiraan ku darista 5-tan qalab ee horumarinta software-ka alaabtooda, iyada oo aan loo eegin luuqadda barnaamijka ee ay isticmaalaan:
1. Habaynta Luuqada Dabiiciga ah (NLP)
Iyada oo la adeegsanayo chatbot-ka hagaajinaysa adeegga macaamiisha, NLP waxay helaysaa dareenka barnaamijyada ka shaqeeya horumarinta software-ka casriga ah. Waxay isticmaalaan qalabyada NLTK sida Python NLTK si ay si dhakhso ah ugu daraan NLP gudaha chatbots, kaaliyeyaasha dhijitaalka ah, iyo alaabta dhijitaalka ah. Badhtamaha 2020 ama mustaqbalka dhow, waxaad arki doontaa NLP oo ka sii muhiimsan wax walba laga bilaabo ganacsiyada tafaariiqda ilaa baabuurta iyo qalabka iskood u madax banaan ee guriga iyo xafiiska.
Ku socoshada agabka horumarinta software-ka iyo teknoolojiyada ka sii wanaagsan, waxaad filan kartaa soosaarayaasha software inay u adeegsadaan NLP siyaabo kala duwan, laga bilaabo is-dhexgalka isticmaale-ku-saleysan ee ku-meel-gaadhka ah ee menu-ka fudud, falanqaynta dareenka, aqoonsiga macnaha guud, dareenka, iyo helitaanka xogta. Waxaas oo dhan waxay heli doonaan inta badan isticmaalayaasha, shirkaduhuna waxay awood u yeelan doonaan inay gaaraan kobaca wax soo saarka ilaa $430 bilyan marka la gaaro 2020 (sida laga soo xigtay IDC, oo ay soo xigatay Deloitte).
2. GraphQL oo beddelaya REST Apis
Sida laga soo xigtay horumariyeyaasha shirkaddayda, oo ah shirkad horumarinta software ee xeebaha, REST API waxay luminaysaa awooddeeda caalamka codsiga sababtoo ah gaabiska xogta ee u baahan in laga sameeyo URL-yo badan si gaar ah.
GraphQL waa isbeddel cusub iyo beddelka ka wanaagsan qaab-dhismeedka ku salaysan REST kaas oo ka soo celiya dhammaan xogta la xidhiidha goobo badan iyadoo la adeegsanayo hal weydiimo. Tani waxay wanaajisaa isdhexgalka macmiilka-server waxayna yaraynaysaa daahitaanka, taasoo ka dhigaysa arjiga mid si aad ah uga jawaaba isticmaalaha.
Waxaad hagaajin kartaa xirfadahaaga horumarinta software marka aad u isticmaasho GraphQL horumarinta software. Intaa waxaa dheer, waxay u baahan tahay kood ka yar REST Api waxayna kuu ogolaaneysaa inaad ku samayso su'aalo adag dhowr sadar oo fudud. Waxa kale oo lagu qalabayn karaa dhawr astaamood oo Backand as a Service (BaaS) ah kuwaas oo fududaynaya in ay isticmaalaan kuwa soo saara software-yada ee luuqadaha barnaamijyada kala duwan, oo ay ku jiraan Python, Node.js, C++ iyo Java.
3. Heer kood hoose/code malaha (code hoose)
Dhammaan qalabka horumarinta koodhka hooseeya waxay bixiyaan faa'iidooyin badan. Waa in ay ahaataa mid hufan sida ugu macquulsan marka la qorayo barnaamijyo badan oo eber ah. Koodhka hoose waxa uu bixiyaa kood hore loo habeeyey kaas oo lagu dhex dari karo barnaamijyo waaweyn. Tani waxay u oggolaaneysaa xitaa kuwa aan barnaamijka ahayn inay si degdeg ah oo sahlan u abuuraan alaabooyin adag oo ay dardargeliyaan nidaamka deegaanka horumarinta casriga ah.
Marka loo eego warbixin TechRepublic ah, aaladaha koodka/koodka hooseeya ayaa mar horeba loogu isticmaalay marinnada shabakadda, nidaamyada software-ka, codsiyada mobaylada iyo meelaha kale. Suuqa aaladaha koodhka hooseeya wuxuu kori doonaa $15 bilyan marka la gaaro 2020. Aaladahani waxay qabtaan wax kasta, oo ay ku jiraan maaraynta macquulka socodka shaqada, shaandhaynta xogta, soo dejinta iyo dhoofinta. Waa kuwan aaladaha kood hooseeya ee ugu wanaagsan 2020:
- Microsoft PowerApps
- Mendix
- Nidaamyada dibadda
- Zoho Abuuraha
- Salesforce App Cloud
- Saldhig Degdeg ah
- Kabaha guga
4. 5G mowjad
Isku xirka 5G wuxuu si weyn u saameyn doonaa abka mobilada iyo horumarinta software iyo sidoo kale horumarinta shabakada. Ka dib oo dhan, teknoolajiyada sida IoT, wax walba waa ku xiran yihiin. Sidaa darteed, software-ka qalabku wuxuu ka faa'iidaysan doonaa awoodda shabakadaha xawaaraha sare leh ee 5G.
Wareysi uu dhawaan siiyey Digital Trends, Dan Dery, oo ah madaxweyne ku xigeenka Motorola ee badeecada, ayaa sheegay in "sanadaha soo socda, 5G ay soo gudbin doonto xogta degdega ah, xawaaraha sare ee xawaaraha, iyo dardargelinta software telefoonka 10 jeer ka dhaqso badan teknoolajiyada wireless jira."
Iftiinkan, shirkadaha software-ku waxay ka shaqayn doonaan inay 5G u keenaan codsiyada casriga ah. Waqtigan xaadirka ah, in ka badan 20 hawl-wadeenno ayaa ku dhawaaqay casriyeyn lagu sameeyay shabakadahooda. Markaa, horumariyayaashu hadda waxay bilaabi doonaan inay ka shaqeeyaan adeegsiga API-yada ku habboon si ay uga faa'iidaystaan ββ5G. Tiknoolajiyadu waxay si weyn u wanaajin doontaa kuwa soo socda:
- Badbaadada barnaamijka shabakadda, gaar ahaan Goynta Shabakadda.
- Bixi habab cusub oo lagu maamulo aqoonsiga isticmaalaha.
- Waxay kuu ogolaanaysaa inaad ku darto hawl cusub codsiyada leh daahitaannimo hoose.
- Waxay saameyn ku yeelan doontaa horumarinta nidaamka AR/VR.
5. Xaqiijinta fudud
Xaqiijinta ayaa si isa soo taraysa u noqonaysa hab wax ku ool ah oo lagu ilaaliyo xogta xasaasiga ah. Farsamada casriga ah kaliya uma nugul in la jabsado software-ka, laakiin sidoo kale waxay taageertaa sirdoonka macmal iyo xitaa xisaabinta quantum. Laakiin suuqa horumarinta software ayaa durba arkaya noocyo badan oo cusub oo xaqiijin ah, sida falanqaynta codka, biometrics iyo aqoonsiga wejiga.
Marxaladdan, haakarisku waxay helayaan habab kala duwan oo ay ku been abuurtaan aqoonsiga isticmaalaha internetka iyo ereyada sirta ah. Mar haddii isticmaaleyaasha mobiladu ay hore u caadeysteen inay talefankooda casriga ah ku galaan sawirka faraha ama sawirka wejiga, sidaas darteed iyagoo isticmaalaya aaladaha aqoonsiga, uma baahnaan doonaan awoodo cusub oo xaqiijin ah maadaama suurtagalnimada tuuganimada internetka ay yaraan doonto. Waa kuwan qaar ka mid ah aaladaha xaqiijinta ee arrimo badan leh oo leh sir SSL.
- Tokens Soft Tokens waxay u rogaan taleefannada gacanta casriga ah sugayayaal dhinacyo badan leh oo ku habboon.
- Qaababka EGrid waa hab fudud in la isticmaalo waana nooc caan ah oo xaqiijinta warshadaha.
- Qaar ka mid ah barnaamijyada xaqiijinta ugu wanaagsan ee ganacsiyada waa RSA SecurID Access, OAuth, Ping Identity, Authx, iyo Aerobase.
Waxaa jira shirkado softiweer ah oo ku yaal Hindiya iyo Mareykanka oo sameynaya cilmi baaris ballaaran oo dhinaca xaqiijinta iyo biometrics ah. Waxay sidoo kale kor u qaadayaan AI si ay u abuuraan software sare oo loogu talagalay codka, wejiga-id, habdhaqanka iyo xaqiijinta biometric. Hadda waxaad ilaalin kartaa kanaalada dhijitaalka ah oo aad hagaajin kartaa awoodaha madal.
gunaanad
Waxay u egtahay in nolosha barnaamij-bixiyeyaashu ay noqon doonto mid dhib yar 2020 maadaama xawaaraha horumarinta software-ku ay u badan tahay inuu sii dardargeliyo. Qalabka la heli karo ayaa noqon doona mid sahlan in la isticmaalo. Ugu dambayntii, horumarkani wuxuu abuuri doonaa adduun firfircoon oo gelaya da' cusub oo dhijitaal ah.
Source: www.habr.com