Vanligvis vil CTRL + + tastene kunne brukes for å øke størrelsen, og CTRL + - for å redusere den.
Har du hjul på musen, kan du bruke CTRL sammen med hjulet for å justere størrelsen. På Mac kan du bruke CMD + + og CMD + -.
Dette kurset har ingen fremtidige kursdato(er) oppført. Bruk skjemaet for å kontakte kursholderen for mer informasjon.
Through a combination of presentations, demos, and hands-on labs, participants get an overview of the Google Cloud platform and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform.
This course teaches participants the following skills:
Module 1: Introducing Google Cloud Platform
-Google Platform Fundamentals Overview
-Google Cloud Platform Big Data Products
Module 2: Compute and Storage Fundamentals
-CPUs on demand (Compute Engine)
-A global filesystem (Cloud Storage)
-CloudShell
-Lab: Set up an Ingest-Transform-Publish data processing pipeline
Module 3: Data Analytics on the Cloud
-Stepping-stones to the cloud
-CloudSQL: your SQL database on the cloud
-Lab: Importing data into CloudSQL and running queries
-Spark on Dataproc
-Lab: Machine Learning Recommendations with Spark on Dataproc
Module 4: Scaling Data Analysis
-Fast random access
-Datalab
-BigQuery
-Lab: Build machine learning dataset
-Machine Learning with TensorFlow
-Lab: Carry out ML with TensorFlow
-Pre-built models for common needs
-Lab: Employ ML APIs
Module 6: Data Processing Architectures
-Message-oriented architectures with Pub/Sub
-Creating pipelines with Dataflow
-Reference architecture for real-time and batch data processing
-Why GCP?
-Where to go from here
-Additional Resources
To get the most of out of this course, participants should have:
This class is intended for the following participants:
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