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This course is part of TensorFlow: Data and Deployment Specialization
Instructor: Laurence Moroney
26,757 already enrolled
(509 reviews)
Recommended experience
Intermediate level
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have basic familiarity with building models in TensorFlow.
(509 reviews)
Recommended experience
Intermediate level
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have basic familiarity with building models in TensorFlow.
Use TensorFlow Serving to do inference over the web
Navigate TensorFlow Hub, a repository of models that you can use for transfer learning
Evaluate how your models work and share model metadata using TensorBoard
Explore federated learning and how to retrain deployed models while maintaining data privacy
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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.
In this final course, you’ll explore four different scenarios you’ll encounter when deploying models. You’ll be introduced to TensorFlow Serving, a technology that lets you do inference over the web. You’ll move on to TensorFlow Hub, a repository of models that you can use for transfer learning. Then you’ll use TensorBoard to evaluate and understand how your models work, as well as share your model metadata with others. Finally, you’ll explore federated learning and how you can retrain deployed models with user data while maintaining data privacy. 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.
12 videos7 readings1 assignment
11 videos8 readings1 assignment1 programming assignment1 ungraded lab
10 videos3 readings1 assignment1 programming assignment1 ungraded lab
9 videos5 readings1 assignment
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Reviewed on Mar 30, 2020
Many useful stuffs if you want to move for Tensorflow or AI Deployment
Reviewed on Oct 10, 2022
Great course! Very important for real world implementation
Reviewed on Jul 4, 2020
great course for utilities to enhance the training and deployment experience
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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.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.