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Learner Reviews & Feedback for Advanced Deployment Scenarios with TensorFlow by DeepLearning.AI

4.8
stars
483 ratings

About the Course

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....

Top reviews

DR

Jun 6, 2020

Enjoyed this specialization as much as I did the Tensorflow in practice. Thank you Laurence Moroney and Andrew Ng for getting these cool topics to all of us, so we can contribute back to community.

DB

May 17, 2020

Great work and I highly recommend this course/specialization! Good job of inserting needed edits to update what's happening in real time.

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51 - 63 of 63 Reviews for Advanced Deployment Scenarios with TensorFlow

By Rani Y

•

May 10, 2023

good

By Egi R T

•

Jun 29, 2022

good

By alfatoni n

•

May 29, 2021

Nice

By Indah D S

•

May 8, 2021

cool

By Ahmad H N

•

May 3, 2021

Good

By Ming G

•

Jun 17, 2020

GJ

By clement l r

•

Mar 18, 2020

A very interesting course to complete Tensorflow deployment option. Most interesting part to me were serving, hub for transfer learning and tensorboard. Maybe Tensorboar could be introduce sooner in other specialization as it sound to be mostly use to discuss model performance, which is extensively discuss in other specialization. Federated Learning seems a little bit extra here, even though it sounds promising.

By Matej M

•

Mar 16, 2021

=This course was much better than the first two. Here were real exercises you had to do and sometimes it was really not easy. It was not just about watching the videos. Also on the discussion forum you were able to search for help.

By Abhiram S

•

Jan 22, 2021

The fact that there were still some problems in the Course regarding technical or exercise based, it shows that this material is relatively new in the domain.

By Chanif R

•

Apr 27, 2022

The lab server is not really great. If there is something wrong in the code,the kernel suddenly restarted, and there is no ouput that described whats wrong

By Elyasaf E

•

Apr 8, 2021

Too theorethical

By Mark P

•

May 2, 2020

This course covers some interesting topics but is far too easy to pass. The programming assignments are really just copy and paste exercises and takes very little time to complete. I found the applications exciting and as an intro to all the new elements of TF it is useful as a whirlwind tour. But apart from the tflite mobil device course which is challenging if you have never used swift/Xcode before it needed to be a bit more than just run throughs of the TF colabs.

By Edwin H

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Nov 9, 2023

The quality of this course is very low compared to the previous specialization. It was not what I expected, it is not taught how to professionally deploy a model