GCP Network Data Processing Models

Google Cloud 2018
  • 10 Videos | 40m 17s
  • Includes Assessment
  • Earns a Badge
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You can create and manage an assortment of data processes and network models using GCP. Explore the various types, including using a GPU and TensorFlow to create and manage GPU and instances.

WHAT YOU WILL LEARN

  • define the types of virtual networks and the benefits of each
    specify the process for creating a network
    recall the process for using TensorFlow with GPU
    describe the various machine learning APIs and their uses
    describe Dataflow and how it can be used to create data processing streams
  • recognize differences between Pub and Sub message middleware and when to use them
    define the various pipelines for Dataflow processing
    demonstrate the process of creating Dataflow pipelines in GCP
    specify the differences between real-time and batch data processing
    recognize more concepts in analysis of data processing in GCP

IN THIS COURSE

  • Playable
    1. 
    Introduction to GCP Networks
    3m 5s
    UP NEXT
  • Playable
    2. 
    Using GCP Models to Create a Network
    4m 36s
  • Locked
    3. 
    Using TensorFlow for Machine Learning
    2m 46s
  • Locked
    4. 
    Using Common Machine Learning APIs
    3m 35s
  • Locked
    5. 
    Processing Data with GCP
    3m 12s
  • Locked
    6. 
    Messaging Middleware Pub and Sub
    3m 43s
  • Locked
    7. 
    Working with GCP Pipelines
    2m 58s
  • Locked
    8. 
    Creating Dataflow Pipelines
    3m 13s
  • Locked
    9. 
    Using Real-time and Batch Data Processing
    3m 9s
  • Locked
    10. 
    Exercise: Analyzing Data Processing
    5m 29s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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