About this Course

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Learner Career Outcomes

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started a new career after completing these courses

18%

got a tangible career benefit from this course

14%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 18 hours to complete
English

What you will learn

  • Compare the key required aspects of a good feature

  • Understand how to preprocess and explore features with Cloud Dataflow and Cloud Dataprep

  • Combine and create new feature combinations through feature crosses

  • Understand and apply how TensorFlow transforms features

Learner Career Outcomes

12%

started a new career after completing these courses

18%

got a tangible career benefit from this course

14%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 18 hours to complete
English

Instructor

Offered by

Placeholder

Google Cloud

Syllabus - What you will learn from this course

Content RatingThumbs Up88%(2,002 ratings)Info
Week
1

Week 1

5 minutes to complete

Introduction to Course

5 minutes to complete
2 videos (Total 5 min)
2 videos
Getting Started with Google Cloud and Qwiklabs3m
5 hours to complete

Raw Data to Features

5 hours to complete
11 videos (Total 36 min), 1 reading, 6 quizzes
11 videos
Raw Data to Features2m
Good vs Bad Features2m
Features Known at Prediction-time3m
Features should be Numeric27s
Features Should Have Enough Examples1m
Bringing Human Insight27s
Representing Features8m
ML vs Statistics3m
Lab Intro: Basic Feature Engineering in BQML33s
Lab Intro: Basic Feature Engineering in Keras30s
1 reading
Resources10m
4 practice exercises
Raw Data to Features and Good vs Bad Features30m
Prediction time, Numeric, Enough Examples, Human sight30m
Representing Features questions30m
Feature Engineering30m
Week
2

Week 2

5 hours to complete

Preprocessing and feature creation

5 hours to complete
9 videos (Total 45 min), 1 reading, 5 quizzes
9 videos
Lab Intro: Simple Dataflow Pipeline19s
Lab Solution: Simple Dataflow Pipeline6m
Data Pipelines that Scale5m
Lab Intro: MapReduce in Dataflow33s
Lab Solution: MapReduce in Dataflow3m
Preprocessing with Cloud Dataprep6m
Lab Intro: Computing Time-Windowed Features in Cloud Data10m
Lab Solution: Computing Time-Windowed Features in Cloud Dataprep36s
1 reading
Resources10m
2 practice exercises
Apache Beam and Cloud Dataflow30m
Preprocessing with Cloud Dataprep30m
Week
3

Week 3

5 hours to complete

Feature Crosses

5 hours to complete
18 videos (Total 64 min), 1 reading, 5 quizzes
18 videos
What is a Feature Cross5m
Discretization1m
Memorization vs. Generalization4m
Taxi colors4m
Lab Intro: Feature Crosses to create a good classifier26s
Lab Solution: Feature Crosses to create a good classifier6m
Sparsity + Quiz5m
Lab Intro: Too Much of a Good Thing31s
Lab Solution: Too Much of a Good Thing7m
Implementing Feature Crosses5m
Embedding Feature Crosses9m
Feature Creation in TensorFlow2m
Feature Creation in DataFlow2m
Lab Intro: Improve ML Model with Feature Engineering42s
Lab Solution: ML Fairness Debrief3m
Lab Intro: Advanced Feature Engineering in BQML51s
Lab Intro: Advanced Feature Engineering in Keras29s
1 reading
Resources10m
2 practice exercises
Feature crosses30m
Module Quiz30m
Week
4

Week 4

2 hours to complete

TensorFlow Transform

2 hours to complete
6 videos (Total 22 min), 1 reading, 2 quizzes
6 videos
TensorFlow Transform8m
Analyze phase3m
Transform phase4m
Supporting serving3m
Lab Intro: Exploring tf.transform1m
1 reading
Resources10m
1 practice exercise
tf.transform30m
1 hour to complete

Summary

1 hour to complete
1 video (Total 7 min), 2 readings, 1 quiz
1 video
2 readings
Resources - Readings Compiled as PDF10m
All Quiz Questions as a PDF10m
1 practice exercise
Course Quiz30m

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About the Machine Learning with TensorFlow on Google Cloud Platform Specialization

Machine Learning with TensorFlow on Google Cloud Platform

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