Questo corso adotta un approccio pratico reale al flusso di lavoro ML attraverso un case study. Un team ML è chiamato a rispondere a numerosi requisiti aziendali e ad affrontare vari casi d'uso ML. Deve comprendere gli strumenti necessari per la gestione e la governance dei dati e considerare l'approccio migliore per la pre-elaborazione dei dati.
Machine Learning in the Enterprise - Italiano
Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Descrivere le opzioni di gestione, governance e pre-elaborazione dei dati.
Identificare quando utilizzare Vertex AutoML, BigQuery ML e l'addestramento personalizzato.
Implementare l'ottimizzazione degli iperparametri mediante Vertex Vizier.
Spiegare come creare previsioni batch e online, configurare il monitoraggio del modello e creare pipeline con Vertex AI.
Details to know
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Recently updated!
April 2025
Assessments
6 assignments
Taught in Italian
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There are 10 modules in this course
Questo modulo fornisce una panoramica del corso e dei suoi obiettivi.
What's included
1 video
Questo modulo descrive il flusso di lavoro aziendale ML e lo scopo di ogni passaggio.
What's included
2 videos1 reading1 assignment
Questo modulo esamina gli strumenti di gestione e governance dei dati aziendali di Google: Feature Store, Data Catalog, Dataplex e Analytics Hub.
What's included
9 videos1 reading1 assignment1 app item
Questo modulo esamina l'arte e la scienza del machine learning e delle reti neurali. Illustra inoltre come addestrare modelli ML personalizzati con Vertex AI.
What's included
7 videos2 readings1 assignment
Questo modulo illustra come ottimizzare gli iperparametri utilizzando Vertex AI Vizier.
What's included
3 videos1 reading1 assignment1 app item
Questo modulo illustra la previsione e il monitoraggio dei modelli di Vertex AI. Innanzitutto, esamineremo le previsioni batch e online utilizzando container predefiniti e personalizzati, quindi passeremo al monitoraggio dei modelli, che è un servizio che aiuta a gestire le prestazioni dei modelli ML.
What's included
4 videos1 reading1 assignment1 app item
Questo modulo illustra le pipeline Vertex AI e come crearle per orchestrare un flusso di lavoro ML.
What's included
3 videos2 readings1 assignment2 app items
Questo modulo esamina le best practice per diversi processi di machine learning in Vertex AI.
What's included
5 videos1 reading
Questo modulo è un riepilogo del corso Machine Learning in the Enterprise.
What's included
4 readings
Questo modulo è un riepilogo della serie di corsi Machine Learning on Google Cloud.
What's included
1 video1 reading
Instructor
Offered by
Recommended if you're interested in Cloud Computing
Google Cloud
Google Cloud
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
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