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Download or read book Probability Induction and Statistics written by Bruno De Finetti and published by John Wiley & Sons. This book was released on 1972 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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Download or read book Supplemento Ai Rendiconti Del Circolo Matematico Di Palermo written by and published by . This book was released on 1906 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Induzione e statistica written by Bruno de Finetti and published by Springer Science & Business Media. This book was released on 2011-06-17 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: B.De Finetti: La probabilità e la statistica nei rapporti con l ́induzione, secondo i diversi punti di vista.- L.J. Savage: La probabilità soggettiva nei problemi pratici della statistica.- L. Daboni: Sulle catene di Markoff.- S. Lombardini: Decisoni economiche in condizioni di incertezza.- A. Longo: La R.O. (Ricerca Operativa).
Download or read book Atti del Congresso internazionale dei fisici written by Congresso internazionale dei fisici and published by . This book was released on 1928 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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Download or read book Bollettino della Unione matematica italiana written by Unione matematica italiana and published by . This book was released on 2005 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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Download or read book Data Science Manuale Italiano Advanced Machine Learning e Deployment written by Mario A. B. Capurso and published by Mario Capurso. This book was released on 2023-09-08 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Questa opera segue il curriculum 2021 della Association for Computing Machinery per specialisti in Scienze dei Dati, con l’obiettivo di costituire un “Bignami” della Scienza ed Ingegneria dei Dati e facilitare il percorso di formazione personale a partire da competenze specialistiche in Informatica o Matematica o Statistica per un lettore di lingua madre italiana. Parte di una serie di testi, riepiloga prima di tutto la metodologia di lavoro standard CRISP DM utilizzata in questa opera e in progetti di Scienza dei Dati. Poichè questo testo utilizza Orange per gli aspetti applicativi, ne descrive l’installazione ed i widget. La fase di modellizzazione dei dati viene considerata nell’ottica dell’apprendimento automatico riepilogando i tipi di apprendimento automatico, i tipi di modelli, i tipi di problemi e i tipi di algoritmi. Sono descritti gli aspetti avanzati associati alla modellizzazione quali le funzioni di perdita e di ottimizzazione come la gradient descent, le tecniche per analizzare le prestazioni dei modelli come il Bootstrapping e la Cross Validation. Vengono analizzati gli scenari di deployment e le più comuni piattaforme, con esempi applicativi. Vengono proposti i meccanismi per automatizzare l’apprendimento automatico e per supportare l’interpretabilità dei modelli e dei risultati come Partial Dependence Plot, Permuted Feature Importance e altre. Gli esercizi sono descritti con Orange e Python con l’uso della libreria Keras/Tensorflow. Il testo è corredato di materiale di supporto ed è possibile scaricare gli esempi in Orange e i dati di prova.
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