GCP Engineering & Streaming Architecture

Google Cloud 2018    |    Intermediate
  • 12 Videos | 1h 15m 17s
  • Includes Assessment
  • Earns a Badge
Likes 63 Likes 63
Feature engineering can be an essential tool in applied machine learning when enhancing a dataset. Explore concepts of feature engineering, including areas of streaming architecture and implementations.

WHAT YOU WILL LEARN

  • describe the concepts of feature engineering
    recall the benefits of quality features with feature engineering and feature selection
    describe the process of input selection in feature engineering
    demonstrate feature engineering in use cases
    recall the concepts of streaming data and real-time stream processing
    describe Dataflow triggers and late data
  • install Java JDK on Windows 10
    demonstrate how to install Apache Maven on Windows 10
    install Google Cloud SDK and initialize SDK Shell on Windows 10
    demonstrate the process of streaming pipelines using Dataflow SDK 2.x and Java in Cloud SDK Shell
    demonstrate the process of streaming pipelines using Dataflow SDK 2.x and Python in Google Cloud Shell
    describe feature engineering concepts and streaming data architecture

IN THIS COURSE

  • Playable
    1. 
    Exploring Features
    4m 2s
    UP NEXT
  • Playable
    2. 
    Benefits of Quality Features
    1m 54s
  • Locked
    3. 
    Input Operations
    6m 9s
  • Locked
    4. 
    Feature Engineering Operations
    3m 54s
  • Locked
    5. 
    Exploring Stream Data
    5m 49s
  • Locked
    6. 
    Exploring Dataflow Triggers and Late Data
    4m 1s
  • Locked
    7. 
    Installing Java JDK on Windows 10
    5m 55s
  • Locked
    8. 
    Installing Apache Maven on Windows 10
    4m 23s
  • Locked
    9. 
    Installing Google Cloud SDK on Windows 10
    5m 9s
  • Locked
    10. 
    Implementing Streaming Pipelines with Java
    10m 1s
  • Locked
    11. 
    Implementing Streaming Pipelines with Python
    13m 4s
  • Locked
    12. 
    Exercise: Features and Streaming Data Models
    5m 27s

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