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DIDATTICO","\u003Ch1 class=\"fw-semibold text-uppercase\">Naive \u003Cspan class=\"text-color-primary-400\">Bayes\u003C/span>\u003C/h1>\n","\u003Cp class=\"font-size-body-1 text-color-grey-800\">Modulo completo su Naive Bayes, dalle basi alla pratica con diverse varianti e applicazioni, inclusa la spam detection.\u003C/p>\n","\u003Ch2>Descrizione\u003C/h2>\n\u003Cp class=\"font-size-body-1\">Questo modulo del corso on demand fornisce una panoramica completa di \u003Cstrong>Naive Bayes\u003C/strong>, un algoritmo di classificazione fondamentale. Inizia con un’introduzione ai\u003Cstrong> concetti base\u003C/strong> e le sue applicazioni nella\u003Cstrong> spam detection\u003C/strong>. Approfondisce le varianti \u003Cstrong>Bernoulli\u003C/strong>, \u003Cstrong>Gaussian\u003C/strong> e \u003Cstrong>Multinomial\u003C/strong>, incluso un approccio “from scratch” per Gaussian Naive Bayes.\u003C/p>\n\u003Cp class=\"font-size-body-1\">Conclude con l’applicazione di Naive Bayes sul dataset \u003Cstrong>MNIST\u003C/strong>, offrendo una solida combinazione di teoria e pratica.\u003C/p>\n",{"title":789,"list":790,"link":783},"DOMANDE FREQUENTI",[791,794,797,800,803,806],{"title":792,"text":793},"Quali competenze sono necessarie per seguire il modulo Naive Bayes?","\u003Cp class=\"fw-regular font-size-body-1\">\u003Cspan class=\"text-color-grey-800\" data-sheets-root=\"1\" data-sheets-value=\"{"1":2,"2":"Per seguire il modulo Naive Bayes sono necessarie competenze preliminari specifiche di Python, Pandas, Numpy, Scikit-learn, Data Visualization."}\" data-sheets-userformat=\"{"2":4482,"4":{"1":2,"2":16750848},"10":2,"11":4,"15":"Arial"}\">Per seguire il modulo Naive Bayes sono necessarie competenze preliminari specifiche di Python, Pandas, Numpy, Scikit-learn, Data Visualization.\u003C/span>\u003C/p>\n",{"title":795,"text":796},"Quali sono i principali argomenti trattati nel modulo Naive Bayes?","\u003Cp class=\"fw-regular font-size-body-1\">\u003Cspan class=\"text-color-grey-800\" data-sheets-root=\"1\" data-sheets-value=\"{"1":2,"2":"Il modulo Naive Bayes copre i seguenti argomenti principali: concetti base di Naive Bayes e l'uso per spam detection, Bernoulli, Gaussian, Multinomial Naive Bayes."}\" data-sheets-userformat=\"{"2":4482,"4":{"1":2,"2":16750848},"10":2,"11":4,"15":"Arial"}\">Il modulo Naive Bayes copre i seguenti argomenti principali: concetti base di Naive Bayes e l’uso per spam detection, Bernoulli, Gaussian, Multinomial Naive Bayes.\u003C/span>\u003C/p>\n",{"title":798,"text":799},"Quali nozioni principali posso apprendere al termine del modulo Naive Bayes?","\u003Cp class=\"fw-regular font-size-body-1\">\u003Cspan class=\"text-color-grey-800\" data-sheets-root=\"1\" data-sheets-value=\"{"1":2,"2":"Al termine del modulo Naive Bayes sarai in grado di comprendere completamente Naive Bayes, un algoritmo fondamentale di classificazione. Questo modulo del corso on demand inizia con un'introduzione ai concetti base e le sue applicazioni nella spam detection. Approfondisce le varianti Bernoulli, Gaussian e Multinomial, incluso un approccio \\"from scratch\\" per Gaussian Naive Bayes. Conclude con l'applicazione di Naive Bayes sul dataset MNIST, offrendo una solida combinazione di teoria e pratica."}\" data-sheets-userformat=\"{"2":4482,"4":{"1":2,"2":16750848},"10":2,"11":4,"15":"Arial"}\">Al termine del modulo Naive Bayes sarai in grado di comprendere completamente Naive Bayes, un algoritmo fondamentale di classificazione. Questo modulo del corso on demand inizia con un’introduzione ai concetti base e le sue applicazioni nella spam detection. Approfondisce le varianti Bernoulli, Gaussian e Multinomial, incluso un approccio “from scratch” per Gaussian Naive Bayes. Conclude con l’applicazione di Naive Bayes sul dataset MNIST, offrendo una solida combinazione di teoria e pratica.\u003C/span>\u003C/p>\n",{"title":801,"text":802},"Al termine del modulo sono previsti un esame finale e una certificazione?","\u003Cp class=\"fw-regular font-size-body-1\">\u003Cspan class=\"text-color-grey-800\" data-sheets-root=\"1\" data-sheets-value=\"{"1":2,"2":"L'esame finale e la certificazione sono previsti per i corsi Data Masters, non per i singoli moduli."}\" data-sheets-userformat=\"{"2":4995,"3":{"1":0},"4":{"1":2,"2":16750848},"10":2,"11":4,"12":0,"15":"Arial"}\">L’esame finale e la certificazione sono previsti per i corsi Data Masters, non per i singoli moduli.\u003C/span>\u003C/p>\n",{"title":804,"text":805},"Il materiale del modulo è scaricabile? Posso rivedere le lezioni?","\u003Cp class=\"fw-regular font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Tutti i materiali (slide, materiale per esercitazioni, ecc.) sono scaricabili, mentre tutte le lezioni possono essere riviste in qualsiasi momento.\u003C/span>\u003C/p>\n",{"title":807,"text":808},"In caso di dubbi e domande, è disponibile assistenza da parte dei docenti?","\u003Cp class=\"fw-regular font-size-body-1\">\u003Cspan class=\"text-color-grey-800\" data-sheets-root=\"1\" data-sheets-value=\"{"1":2,"2":"Certamente, durante il modulo Naive Bayes è disponibile assistenza continua da parte dei nostri docenti per qualsiasi dubbio o domanda."}\" data-sheets-userformat=\"{"2":4482,"4":{"1":2,"2":16750848},"10":2,"11":4,"15":"Arial"}\">Certamente, durante il modulo Naive Bayes è disponibile assistenza continua da parte dei nostri docenti per qualsiasi dubbio o domanda.\u003C/span>\u003C/p>\n",[810,813,817,820],{"icon":811,"caption":71,"text":812},"icon-level","Da Beginner ad Advanced",{"icon":814,"caption":815,"text":816},"icon-round-check","PREREQUISITI","Python per la ds, Pandas, Numpy, Scikit-learn, Data visualization",{"icon":818,"caption":70,"text":819},"icon-calendar","4 ore",{"icon":821,"caption":822,"text":823},"icon-lessons","LEZIONI","100% on demand",[825],{"title":745,"items":826},[827,830,832,834,836,838,840,842],{"title":828,"text":829},"Introduzione e concetti base su Naive Bayes","\u003Cp>\u003Cspan class=\"text-color-grey-700\">Nessun dettaglio\u003C/span>\u003C/p>\n",{"title":831,"text":829},"Naive Bayes per la spam detection",{"title":833,"text":829},"Approfondimento Naive Bayes",{"title":835,"text":829},"Bernoulli Naive Bayes",{"title":837,"text":829},"Gaussian Naive Bayes",{"title":839,"text":829},"Gaussian Naive Bayes from scratch",{"title":841,"text":829},"Multinomial Naive Bayes e Bag of Words",{"title":843,"text":829},"Naive Bayes per MNIST",{"list":845,"intro":1005},[846,898,988],{"id":335,"date":847,"title":332,"description":848,"url":333,"image":849,"duration":857,"prerequisite":858,"regular_price":859,"taxonomies":860,"level":271,"type":169},"2024-06-04T16:10:06+02:00","Algoritmi di Machine Learning è il corso per apprendere tutti gli algoritmi di Machine Learning con Python. 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