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Internet of Things with Python
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InteractwiththeworldandrapidlyprototypeIoTapplicationsusingPythonAboutThisBook?RapidlyprototypeevencomplexIoTapplicationswithPythonandputthemtopracticaluse?EnhanceyourIoTskillswiththemostup-to-dateapplicabilityinthefieldofwearabletech,smartenvironments,andhomeautomation?Interactwithhardware,sensors,andactuatorsandcontrolyourDIYIoTprojectsthroughPythonWhoThisBookIsForThebookisidealforPythondeveloperswhowanttoexplorethetoolsinthePythonecosysteminordertobuildtheirownIoTapplicationsandworkonIoT-relatedprojects.ItisalsoaveryusefulresourcefordeveloperswithexperienceinotherprogramminglanguagesthatwanttoeasilyprototypeIoTapplicationswiththeIntelGalileoGen2board.WhatYouWillLearn?PrototypeanddevelopIoTsolutionsfromscratchwithPythonastheprogramminglanguage?DevelopIoTprojectswithIntelGalileoGen2boardalongwithPython?WorkwiththedifferentcomponentsincludedintheboardsusingPythonandtheMRAAlibrary?Interactwithsensors,actuators,andshields?WorkwithUARTandlocalstorage?InteractwithanyelectronicdevicethatsupportstheI2Cbus?Allowmobiledevicestointeractwiththeboard?Workwithreal-timeIoTandcloudservices?UnderstandBigDataandIoTanalyticsInDetailInternetofThings(IoT)isrevolutionizingthewaydevices/thingsinteractwitheachother.AndwhenyouhaveIoTwithPythononyourside,you'llbeabletobuildinteractiveobjectsanddesignthem.Thisbookletsyoustayattheforefrontofcutting-edgeresearchonIoT.We'llopenupthepossibilitiesusingtoolsthatenableyoutointeractwiththeworld,suchasIntelGalileoGen2,sensors,andotherhardware.Youwilllearnhowtoread,write,andconvertdigitalvaluestogenerateanalogoutputbyprogrammingPulseWidthModulation(PWM)inPython.Youwillgetfamiliarwiththecomplexcommunicationsystemincludedintheboard,soyoucaninteractwithanyshield,actuator,orsensor.Lateron,youwillnotonlyseehowtoworkwithdatareceivedfromthesensors,butalsoperformactionsbysendingthemtoaspecificshield.You'llbeabletoconnectyourIoTdevicetotheentireworld,byintegratingWiFi,Bluetooth,andInternetsettings.Witheverythingready,youwillseehowtoworkinrealtimeonyourIoTdeviceusingtheMQTTprotocolinpython.Bytheendofthebook,youwillbeabletodevelopIoTprototypeswithPython,libraries,andtools.StyleandapproachThisbooktakesatutorial-likeapproachwithmissioncriticalchapters.Theinitialchaptersareintroductionsthatsetthepremiseforusefulexamplescoveredinlaterchapters.

Gastón C. Hillar ·數(shù)據(jù)庫 ·8.6萬字

七周七數(shù)據(jù)庫
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如今,我們要面對(duì)和使用的數(shù)據(jù)正在變得越來越龐大和復(fù)雜。如果說數(shù)據(jù)是新的石油。那么數(shù)據(jù)庫就是油田、煉油廠、鉆井和油泵。作為一名現(xiàn)代的軟件開發(fā)者,我們需要了解數(shù)據(jù)管理的新領(lǐng)域,既包括RDBMS,也包括NoSQL。《七周七數(shù)據(jù)庫》遵循《七周七語言》的寫作風(fēng)格和體例,帶領(lǐng)你學(xué)習(xí)和了解當(dāng)令最熱門的開源數(shù)據(jù)庫。在簡單的介紹之后,《七周七數(shù)據(jù)庫》分章介紹了7種數(shù)據(jù)庫。這些數(shù)據(jù)庫分別屬于5種不同的數(shù)據(jù)庫風(fēng)格,但每種數(shù)據(jù)庫都有自己保存數(shù)據(jù)和看待世界的方式。它們依次是PostgreSQL、Riak、ApacheHBase、MongoDB、ApacheCouchDB、Neo4J和Redis。《七周七數(shù)據(jù)庫》將深入每一種數(shù)據(jù)庫,介紹它們的優(yōu)勢和不足,以及如何選取一種最符合你的應(yīng)用需求的數(shù)據(jù)庫。《七周七數(shù)據(jù)庫》適合數(shù)據(jù)庫架構(gòu)師、數(shù)據(jù)庫管理員,以及想要了解和學(xué)習(xí)各種NoSQL數(shù)據(jù)庫技術(shù)的程序員閱讀。《七周七數(shù)據(jù)庫》將幫助讀者了解、選擇和應(yīng)用這些數(shù)據(jù)庫,從而更好地發(fā)揮日益增長的大數(shù)據(jù)的能力。

(美)Eric Redmond Jim R.Wilson ·數(shù)據(jù)庫 ·14.7萬字

Architects of Intelligence
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FinancialTimesBestBooksoftheYear2018TechRepublicTopBooksEveryTechieShouldReadBookDescriptionHowwillAIevolveandwhatmajorinnovationsareonthehorizon?Whatwillitsimpactbeonthejobmarket,economy,andsociety?Whatisthepathtowardhuman-levelmachineintelligence?Whatshouldwebeconcernedaboutasartificialintelligenceadvances?ArchitectsofIntelligencecontainsaseriesofin-depth,one-to-oneinterviewswhereNewYorkTimesbestsellingauthor,MartinFord,uncoversthetruthbehindthesequestionsfromsomeofthebrightestmindsintheArtificialIntelligencecommunity.Martinhaswide-rangingconversationswithtwenty-threeoftheworld'sforemostresearchersandentrepreneursworkinginAIandrobotics:DemisHassabis(DeepMind),RayKurzweil(Google),GeoffreyHinton(Univ.ofTorontoandGoogle),RodneyBrooks(RethinkRobotics),YannLeCun(Facebook),Fei-FeiLi(StanfordandGoogle),YoshuaBengio(Univ.ofMontreal),AndrewNg(AIFund),DaphneKoller(Stanford),StuartRussell(UCBerkeley),NickBostrom(Univ.ofOxford),BarbaraGrosz(Harvard),DavidFerrucci(ElementalCognition),JamesManyika(McKinsey),JudeaPearl(UCLA),JoshTenenbaum(MIT),RanaelKaliouby(Affectiva),DanielaRus(MIT),JeffDean(Google),CynthiaBreazeal(MIT),OrenEtzioni(AllenInstituteforAI),GaryMarcus(NYU),andBryanJohnson(Kernel).MartinFordisaprominentfuturist,andauthorofFinancialTimesBusinessBookoftheYear,RiseoftheRobots.HespeaksatconferencesandcompaniesaroundtheworldonwhatAIandautomationmightmeanforthefuture.MeetthemindsbehindtheAIsuperpowersastheydiscussthescience,businessandethicsofmodernartificialintelligence.ReadJamesManyika’sthoughtsonAIanalytics,GeoffreyHinton’sbreakthroughsinAIprogramminganddevelopment,andRanaelKaliouby’sinsightsintoAImarketing.ThisAIbookcollectstheopinionsoftheluminariesoftheAIbusiness,suchasStuartRussell(coauthoroftheleadingAItextbook),RodneyBrooks(aleaderinAIrobotics),DemisHassabis(chessprodigyandmindbehindAlphaGo),andYoshuaBengio(leaderindeeplearning)tocompleteyourAIeducationandgiveyouanAIadvantagein2019andthefuture.

Martin Ford ·數(shù)據(jù)庫 ·19.7萬字

一類智能優(yōu)化算法的改進(jìn)及應(yīng)用研究
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智能優(yōu)化算法以其解決實(shí)際問題的有效性而快速發(fā)展起來,憑借著算法簡單、容易實(shí)現(xiàn)、易與其他學(xué)科相結(jié)合等優(yōu)點(diǎn),智能優(yōu)化算法被越來越多的專家與學(xué)者所認(rèn)可并應(yīng)用。首先,本書闡述了優(yōu)化理論的相關(guān)內(nèi)容,然后對(duì)智能優(yōu)化算法進(jìn)行綜述,并重點(diǎn)介紹了粒子群優(yōu)化算法與和聲搜索算法。其次,將局部尋優(yōu)能力較好的變尺度法與粒子群算法結(jié)合,提出了基于變尺度的粒子群優(yōu)化算法,同時(shí)將其應(yīng)用于非線性方程組的求解。然后,將改進(jìn)后的算法應(yīng)用于偏微分方程的求解中,將傳統(tǒng)的有限差分法進(jìn)行改進(jìn),并與改進(jìn)后的粒子群算法進(jìn)行結(jié)合求解偏微分方程,通過數(shù)值算例對(duì)其進(jìn)行驗(yàn)證。再次,將和聲搜索算法與局部搜索能力較好的變尺度法相結(jié)合,提出了基于變尺度的和聲搜索算法。通過數(shù)值實(shí)驗(yàn)驗(yàn)證改進(jìn)后的算法尋優(yōu)能力較強(qiáng),魯棒性較好,而且方法容易實(shí)現(xiàn)。最后,探討了將微分方程轉(zhuǎn)化為變分問題的方法,將求解微分方程的權(quán)余量方法與標(biāo)準(zhǔn)粒子群算法進(jìn)行結(jié)合,提出了一種新的求解優(yōu)化問題的方法。同時(shí),在結(jié)合傳統(tǒng)的最小二乘近似解法與粒子群算法的基礎(chǔ)上,提出了結(jié)合粒子群算法和最小二乘法求解變分優(yōu)化問題的新方法。給出改進(jìn)思路、計(jì)算流程后,通過仿真實(shí)驗(yàn)發(fā)現(xiàn)改進(jìn)的兩種變分優(yōu)化算法有較強(qiáng)的適用性。

齊微 ·數(shù)據(jù)庫 ·7.1萬字

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