Data Pipelines with TensorFlow Data Services (Coursera)

Data Pipelines with TensorFlow Data Services (Coursera)
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We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow
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Data Pipelines with TensorFlow Data Services (Coursera)
Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model.

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In this third course, you will:

- Perform streamlined ETL tasks using TensorFlow Data Services

- Load different datasets and custom feature vectors using TensorFlow Hub and TensorFlow Data Services APIs

- Create and use pre-built pipelines for generating highly reproducible I/O pipelines for any dataset

- Optimize data pipelines that become a bottleneck in the training process

- Publish your own datasets to the TensorFlow Hub library and share standardized data with researchers and developers around the world

This Specialization builds upon our TensorFlow in Practice Specialization. If you are new to TensorFlow, we recommend that you take the TensorFlow in Practice Specialization first. To develop a deeper, foundational understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.


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


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


Course 3 of 4 in the TensorFlow: Data and Deployment Specialization.


Syllabus


WEEK 1

Data Pipelines with TensorFlow Data Services

This week, you will be able to perform efficient ETL tasks using Tensorflow Data Services APIs


WEEK 2

Splits and Slices API for Datasets in TF

In this week, you will construct train/validation/test splits of any dataset - either custom or present in TensorFlow hub dataset library - using Splits API


WEEK 3

Exporting Your Data into the Training Pipeline

This week you will extend your knowledge of data pipelines


WEEK 4

Performance

You'll learn how to handle your data input to avoid bottlenecks, race conditions and more!



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

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.