Chevron Left
Back to Advanced Deployment Scenarios with TensorFlow

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

4.8
stars
508 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

RN

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.

Filter by:

1 - 25 of 66 Reviews for Advanced Deployment Scenarios with TensorFlow

By seyed r m

•

Feb 13, 2020

I found this course to be a great introduction to the wide range of features provided by TensorFlow in the context of (i) model serving (ii) sharing models (iii) tensor board and (iv) federated learning. It provided me with an opportunity to focus my attention on these topics, to form a holistic view of the subjects rather than randomly reading documentation on an adhoc basis. Keep up the good work and thanks for keeping the length of the videos short and concise.

By Michael M

•

Feb 14, 2020

Enjoyed the course, the balance between the quiz and the practicals well set. It gives you a ran of your money. Plus people who are helpful like Alexander Ivanov. Who helped everyone especially for the week 2 assignment. I learned a lot and will use it to my best interest to also help others. Thank you team. Maybe the mentors need to contribute more. It would add more value.

By Sayak P

•

Feb 12, 2020

I absolutely enjoyed the entire specialization and here's why - I find it easier to understand stuff with readable code and all of the courses in this specialization contain a ton of useful and effective code snippets. Besides that, the courses have tons of commentary about common practicalities.

By Martín C

•

Jun 12, 2020

¡Excelente curso! Recomendado para quienes quieren estar informado sobre los aspectos más avanzados y modernos de TensorFlow. ¡Recomendado!

Excellent course! Recommended for those who want to be informed about the most advanced and modern aspects of TensorFlow. Recommended!

By Moustafa S

•

Jul 5, 2020

great course for utilities to enhance the training and deployment experience

By Suresh K M

•

Apr 10, 2020

This topic seems to be very important but the content is not as good as rest of the weeks content, more explanations and more simple examples could have helped

By Pavel

•

Mar 5, 2020

In general course is quite useful, especially Weeks 1 and 2. However content for week 3 - tensorboard - seems artificial (especially logging confusion matrix in TensorBoard) and not related to deployment at all. And Week 4 has really great topic, however the content is very poor. The most useful are the links, for which I suppose one could just google.

By Victor A N P

•

Sep 7, 2020

It is decent, but it is just a shadow of how good the Tensorflow Developer Professional Certificate is.

Many of the programming assignments are bugged. You don't have enough opportunities to practice before the programming assignment. Most of the videos are just codes being quickly explained. I deeply respect Andrew Ng and Laurence, but this specialization is not as good as the previous one.

By Oussama B

•

Apr 3, 2020

DIsapointed..

By Juan P J A

•

Oct 10, 2022

An interesting course taught by Laurence Moroney introducing a wide range of topics on deployment scenarios and efficient data pipelines. It is a fun course with hands-on deployment on the browser, Android and Raspberry Pi, and efficient data pipelines, tf datasets, and tf_hub models. Given the wide coverage, it requires further dedication to dive into the different topics. It includes four courses: -Browser-device models with tensorflow.js: Perform inference and training using JavaScript. Convert models to json format. -Device-based with tensorflow.lite: Convert models to tflite format (low latency, size and power consumption). Running models on Android, iOS, and embedded devices. -Data pipelines with tensorflow data services: tfds datasets and pipelines, improving data pipelines performance. -Advanced deployment scenarios:  Model inference over the web by server request using Tensorflow Serving. Pretrained models with TF hub. Callbacks during training using Tensorboard. Introduction to decentralized edge device training with TFFederated Learning.

By Rick T

•

May 11, 2021

Great course on TensorFlow, TensorFlow.js and TensorFlow Lite! The section on TensorFlow Federated Learning was especially interesting and with privacy issues being a major consideration, Federated Learning offers a great way to take advantage of the billions of IoT devices and enhance privacy at the same time.

By AKSHAY K C

•

Apr 13, 2020

Another really good course by the instructor to end the course enlightening on the recent concepts of TensorFlow Serving, TensorFlow hub, TensorBoard, and Federated Learning. Kudos to the entire team for coming up with such a good course on advanced concepts.

By Okta F S

•

Oct 3, 2020

This is very cool course. We will learn a lot about how to serving our model, publish our model to tensorflow hub, how to using tensorboard with callback, and also we will learn about advance topic federated learning and how to use the API on tensorflow.

By Krzysztof S

•

Oct 17, 2024

I could not run collabs online, and locally there are problems with the newest version of tensorflow and other libraries, there is no requirement.txt file to run correct setup. There's always something new to learn, still 5 stars in 2024

By Rohit N

•

Jun 7, 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.

By Dave W B

•

May 18, 2020

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

By Jiten S

•

Nov 10, 2021

Grader messages are not helpful due to which debugging time increases. Rest the course is quite informational and useful.

By Ernesto C

•

Mar 24, 2020

Very clear, the pace is right, content is very interesting and classes are engaging. What else is to desire? :)

By Nur M H

•

May 11, 2023

It's a great course that covers a lot of ground and is delivered in a clear and easy-to-understand way.

By Adrian P S

•

Mar 8, 2020

ver good course to get first insights for orientation and later deep dives. I like it very much!

By Pachi C

•

Apr 12, 2020

Fantastic course, very recomendable for advanced TensorFlow applications!!!

By Muhammad S

•

May 3, 2020

Very practical and advanced topics taught in easily understandable way.

By Chun Y Y

•

Mar 31, 2020

Many useful stuffs if you want to move for Tensorflow or AI Deployment

By Muhammad A

•

Dec 2, 2020

If you want to learn extra libraries of tensorflow then take this

By Angshuman S

•

May 16, 2020

Awesome course for the using and application of Machine learning