Introduzione a Data Science Workspace per Data Scientist

Scopri di più su Data Science Workspace in Adobe Experience Platform. Questa playlist è progettata per i data scientist che desiderano imparare a utilizzare JupyterLab Notebooks per ricavare informazioni approfondite ed eseguire query sui dati, creare set di dati abilitati per il profilo, pubblicare modelli automatizzati di apprendimento automatico e attivare informazioni acquisite da computer sia per le applicazioni Adobi che per quelle non Adobi.

https://video.tv.adobe.com/v/3412912?learn=on

Panoramica di Data Science Workspace

L’obiettivo dell’apprendimento automatico su Adobe Experience Platform è quello di democratizzare la scienza dei dati utilizzando l’esperienza nel settore dei prodotti Adobi, dei clienti e dei partner per creare un ecosistema di servizi intelligenti per alimentare la prossima generazione di esperienze dei clienti. Data Science Workspace semplifica l’accesso a dati omni-channel, la creazione di modelli, l’operazionalizzazione dei modelli con un’implementazione con un solo clic e l’utilizzo di informazioni sui modelli condividendoli tramite profili cliente in tempo reale. Questo video offre una panoramica di Data Science Workspace e del suo valore per le aziende.

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https://video.tv.adobe.com/v/332368?learn=on

Panoramica dell’architettura di Data Science Workspace

Questo video descrive l’architettura generale e illustra i componenti principali di Data Science Workspace in Adobe Experience Platform.

281

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https://video.tv.adobe.com/v/333312?learn=on

Creare lo schema e il set di dati del corso

Scopri come creare il set di dati e lo schema del corso Data Science Workspace utilizzati nel resto del corso.

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https://video.tv.adobe.com/v/345258?learn=on

Caricare dati nei notebook JupyterLab

Questo video mostra come creare un notebook JupyterLab e caricare dati da Adobe Experience Platform. Viene inoltre illustrato come aumentare le prestazioni del notebook quando si lavora con grandi quantità di dati.

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https://video.tv.adobe.com/v/333311?learn=on

Eseguire query e individuare dati in Data Science Workspace

Adobe Experience Platform consente di utilizzare SQL (Structured Query Language) in Data Science Workspace integrando Query Service in JupyterLab come funzione standard.

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Analisi esplorativa dei dati in Data Science Workspace

L’esercitazione Exploratory Data Analysis (EDA) è stata progettata per aiutarti a individuare pattern nei dati, a verificare la correttezza dei dati e a riepilogare i dati rilevanti per i modelli predittivi.

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Panoramica su ricette, modelli e servizi

Scopri le ricette, i modelli e i servizi in Adobe Experience Platform Data Science Workspace.

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https://video.tv.adobe.com/v/333427?learn=on

Analizzare le prestazioni del modello

Scopri alcuni dei diversi metodi utilizzati per analizzare le prestazioni di un modello, ad esempio una matrice di confusione, Precisione, Richiamo e Precisione.

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Creare un modello utilizzando il modello per la generazione di formule

Questo video illustra come utilizzare il modello per la generazione di formule del modulo di avvio JupyterLab per addestrare e valutare un modello di propensione e creare una ricetta.

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https://video.tv.adobe.com/v/333595?learn=on

Creare e pubblicare un modello addestrato

Scopri come creare, addestrare, valutare e pubblicare un modello utilizzando una ricetta creata con il notebook JupyterLab per la generazione di ricette.

184

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Pianificazione dell’apprendimento e del punteggio automatizzati per un servizio

Scopri come impostare la formazione e il punteggio automatizzati per un servizio in Data Science Workspace.

172

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Utilizzare l’output di apprendimento automatico nella segmentazione

Scopri come gli output del modello Data Science Workspace possono essere utilizzati nel profilo cliente in tempo reale e nella segmentazione.

387

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