{"id":51845,"date":"2020-11-15T07:00:13","date_gmt":"2020-11-15T06:00:13","guid":{"rendered":"http:\/\/smeupnew.it\/magazine\/blog\/data-science-semplificata-h2o-driverless-ai\/"},"modified":"2021-04-12T09:21:45","modified_gmt":"2021-04-12T07:21:45","slug":"h2o-driverless-ai","status":"publish","type":"post","link":"https:\/\/www.smeup.com\/magazine\/blog\/h2o-driverless-ai\/","title":{"rendered":"Non solo acqua: la data science semplificata di H2O Driverless AI"},"content":{"rendered":"

H2O Driverless AI \u00e8 una piattaforma studiata per rendere pi\u00f9 semplice e rapido il processo di integrazione e utilizzo del machine learning all\u2019interno delle aziende.<\/span>
\n<\/span>La tecnologia driverless consente alle aziende di non avere pi\u00f9 bisogno di svolgere un ampio lavoro di progettazione di funzioni iniziale; inoltre permette di automatizzare la convalida e l’ottimizzazione dei modelli.<\/span>
\n<\/span>H2O Driverless AI \u00e8 in grado di automatizzare quasi tutti i processi che generalmente compongono un progetto di machine learning:\u00a0<\/span><\/p>\n

    \n
  1. Data Visualization\u00a0<\/span><\/li>\n
  2. Feature Engineering<\/span><\/li>\n
  3. Model Selection\u00a0<\/span><\/li>\n
  4. Model Tuning\u00a0<\/span><\/li>\n
  5. Automatic Scoring Pipeline\u00a0<\/span><\/li>\n
  6. Machine Learning Interpretability\u00a0<\/span><\/li>\n
  7. Deployment<\/span><\/li>\n<\/ol>\n

    Ecco di seguito un esempio di workflow in cui \u00e8 coinvolto un sistema Driverless AI:<\/span><\/b><\/p>\n<\/div>

    \"smeup<\/span><\/div>

    Semplificazione e automatizzazione dei processi<\/h2>\n

    Vediamo pi\u00f9 nello specifico in che modo H2O Driverless AI riesce a semplificare e\u00a0 automatizzare i processi all\u2019interno di un progetto di machine learning.<\/span><\/p>\n

    Data Visualization\u00a0<\/span><\/h3>\n

    H2O Driverless AI \u00e8 in grado di creare in maniera automatica grafici di differenti tipologie per analizzare i dati, le correlazioni tra le variabili, la distribuzione di ogni variabile. E\u2019 in grado inoltre di fornire consigli circa le trasformazioni da applicare ad una o pi\u00f9 variabili.<\/span><\/p>\n

    Feature Engineering<\/h3>\n

    H2O Driverless AI \u00e8 in grado di testare automaticamente diverse trasformazioni delle variabili, raggrupparle, trasformarle con trasformatori differenti a seconda delle diverse tipologie di dati, creare nuove variabili combinandole tra loro e molto altro ancora, garantendo un alto livello di accuratezza.<\/span><\/p>\n

    Model Selection \/ Model Tuning<\/h3>\n

    Per quanto riguarda la selezione del modello da utilizzare, H2O \u00e8 in grado di individuare un gruppo di modelli a seconda della tipologia di target (Classificazione, Regressione etc..), scegliere i modelli e aggiustarne i parametri(model tuning) per ottenere il minor tasso di errore.<\/span><\/p>\n

    Machine Learning Interpretability<\/h3>\n

    H2O Driverless AI attraverso la Machine Learning Interpretability \u00e8 capace di individuare e mostrare mostra quale variabile ha avuto un impatto negativo o positivo sul modello, in base a quale ragionamento il modello ha fatto quelle previsioni, quale modello \u00e8 stato utilizzato e perch\u00e9 e molto altro ancora.<\/span><\/p>\n

    Deployment<\/h3>\n

    Al termine del processo, H2O Driverless AI crea la Scoring Pipeline all\u2019interno della quale \u00e8 riportato il modello migliore. La scoring pipeline rappresenta il prodotto finito che pu\u00f2 essere trasposto su cloud o scaricato in locale.<\/span><\/p>\n

    Aziz Ur Rehman
    \n<\/strong>R&D Department Intern – smeup
    \n<\/em>My LinkedIn Profile<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"

    H2O Driverless AI \u00e8 una piattaforma studiata per rendere pi\u00f9 semplice e rapido il processo di integrazione e utilizzo del machine learning all\u2019interno delle aizende.<\/p>\n","protected":false},"author":1,"featured_media":54239,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[7166],"tags":[],"class_list":["post-51845","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-machine-learning"],"acf":[],"yoast_head":"\nNon solo acqua: la data science semplificata di H2O Driverless AI<\/title>\n<meta name=\"description\" content=\"H2O Driverless AI \u00e8 una piattaforma studiata per rendere pi\u00f9 semplice e rapido il processo di integrazione e utilizzo del machine learning in azienda.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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