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.
Data Pipelines with TensorFlow Data Services
Data Pipelines with TensorFlow Data Services
This course is part of TensorFlow: Data and Deployment Specialization
Instructor: Laurence Moroney
28,008 already enrolled
Gain insight into a topic and learn the fundamentals.
4.5
(529 reviews)
Intermediate level
Recommended experience
Flexible schedule
Approx. 11 hours
Learn at your own pace
93%
Most learners liked this course
What you'll 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'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
5 assignments
Taught in English
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This course is part of the TensorFlow: Data and Deployment Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
This week, you will be able to perform efficient ETL tasks using Tensorflow Data Services APIs
What's included
10 videos6 readings1 assignment1 programming assignment
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
What's included
7 videos4 readings1 assignment1 programming assignment
This week you will extend your knowledge of data pipelines
What's included
21 videos6 readings1 assignment1 programming assignment
You'll learn how to handle your data input to avoid bottlenecks, race conditions and more!
What's included
22 videos4 readings2 assignments1 programming assignment1 ungraded lab
Instructor
Instructor ratings
4.8 (51 ratings)Offered by
Recommended if you're interested in Software Development
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Learner reviews
4.5
529 reviews
- 5 stars
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18.11%
- 3 stars
8.11%
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3.58%
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2.26%
Showing 3 of 529
SS
4
Reviewed on Oct 2, 2020
Just what i needed. Would have gotten 5 starts, if they fix the last lab.
RR
5
Reviewed on Jul 7, 2020
First 3 weeks are really nice but for me week 4 was a bit tough with very less explanation
AD
5
Reviewed on Feb 2, 2020
Excellent course both for Data Scientists and Machine Learning Engineers!
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Frequently asked questions
Changes in TensorFlow API: Since this Specialization was launched in early 2020, there have been changes to the TensorFlow API which affect the material in Weeks 1 and 2. With this refresh, you can access updated lectures, quizzes, and assignments.
Changing the Difficulty Level of Assignments: Based on valuable learner feedback, we’ve revised the Week 4 assignments to ensure that you have a full grasp of the foundational principles and are well-prepared to tackle them.
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.