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Data Science e Machine Learning: Dai dati alla conoscenza

Data Science e Machine Learning: Dai dati alla conoscenza

          
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About the Book

Estrarre conoscenza dalle informazioni attraverso l'analisi dei dati: quella del data scientist è stata definita la professione più attraente del XXI secolo. Analizzare le relazioni tra i dati, scoprire nuove informazioni e, con l'aiuto del machine learning, sfruttare l'enorme potenziale che vi si nasconde costruendo modelli previsionali.
In questo libro illustriamo le tecniche di analisi dei dati e di costruzione di algoritmi di Machine Learning e Deep Learning, passando dalle conoscenze teoriche alle applicazioni con il software statistico R, tramite ampi esempi pratici.

Cosa imparerai

  • Matematica e algebra per il machine learning
  • Utilizzo del software statistico R e R-Studio
  • Statistica descrittiva e inferenziale per la data science
  • Calcolo delle probabilità
  • La preparazione dei dati e la feature engineering
  • Progettare e validare gli algoritmi di machine learning
  • Algoritmi di regressione, classificazione e clustering
  • Fare previsioni basate su serie temporali
  • I modelli di reti neurali e deep learning
  • Raccontare i dati: data visualization & data storytelling
A chi è rivolto questo libro
Questo libro è rivolto a chiunque voglia imparare a manipolare ed analizzare i dati traendo da questi nuova conoscenza. Se sei un manager IT o un analista che vuole entrare nel mondo della Data Science e dei Big Data, se sei uno sviluppatore che vuole conoscere le nuove tendenze nel campo dell'Intelligenza Artificiale o sei semplicemente curioso di conoscere questo mondo, allora questo libro è per te.

Contenuti

  • La data science e i modelli di analisi
  • La gestione dei big data
  • Analisi univariata e multivariata, probabilità e test d'ipotesi
  • Esplorare e visualizzare i dati
  • Preparazione e pulizia dei dati
  • Apprendimento supervisionato: classificazione e regressione
  • Apprendimento non supervisionato: clustering e riduzione dimensionale
  • Apprendimento semi supervisionato
  • Algoritmi di associazione e analisi delle serie temporali
  • Misure di validazione ed ottimizzazione degli algoritmi
  • Le reti neurali e il Deep Learning
  • Reti Convoluzionali per il riconoscimento di immagini
  • Reti Ricorrenti e LSMT per le sequenze
  • Encoders per la feature selection
  • Algoritmi generativi


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Product Details
  • ISBN-13: 9798463647184
  • Publisher: Independently Published
  • Binding: Paperback
  • Language: Italian
  • Returnable: N
  • Sub Title: Dai dati alla conoscenza
  • Width: 178 mm
  • ISBN-10: 8463647189
  • Publisher Date: 10 Sep 2021
  • Height: 254 mm
  • No of Pages: 488
  • Spine Width: 25 mm
  • Weight: 838 gr


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