About this Course

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Intermediate Level

We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow

Approx. 11 hours to complete
English

What you will learn

  • Perform efficient ETL tasks using Tensorflow Data Services APIs

  • Construct train/validation/test splits of any dataset - either custom or present in TensorFlow Hub Dataset library - using Splits API

  • Use different modules and functions of the TFDS API to prepare your data for training pipelines

  • Identify bottlenecks in your input pipelines and increase your workflow efficiency by input parallelization

Skills you will gain

Artificial Neural NetworkTensorflowExtraction, Transformation And Loading (ETL)Data PipelinesTensorFlow Datasets
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level

We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow

Approx. 11 hours to complete
English

Instructor

Offered by

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DeepLearning.AI

Syllabus - What you will learn from this course

Content RatingThumbs Up91%(1,001 ratings)Info
Week
1

Week 1

3 hours to complete

Data Pipelines with TensorFlow Data Services

3 hours to complete
10 videos (Total 21 min), 4 readings, 2 quizzes
Week
2

Week 2

2 hours to complete

Splits and Slices API for Datasets in TF

2 hours to complete
7 videos (Total 26 min), 3 readings, 2 quizzes
Week
3

Week 3

3 hours to complete

Exporting Your Data into the Training Pipeline

3 hours to complete
21 videos (Total 44 min), 5 readings, 2 quizzes
Week
4

Week 4

3 hours to complete

Performance

3 hours to complete
22 videos (Total 44 min), 2 readings, 3 quizzes

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About the TensorFlow: Data and Deployment Specialization

TensorFlow: Data and Deployment

Frequently Asked Questions

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