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.
Status: Transfer Learning
Transfer Learning
Status: Machine Learning
Machine Learning
Intermediate·Course·13 hours
Featured reviews
5.0
·Reviewed Oct 10, 2022
Great course! Very important for real world implementation
4.0
·Reviewed 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
5.0
·Reviewed Nov 9, 2021
Grader messages are not helpful due to which debugging time increases. Rest the course is quite informational and useful.
5.0
·Reviewed Jul 4, 2020
great course for utilities to enhance the training and deployment experience
5.0
·Reviewed Jul 29, 2022
Excellent Content. It Will definitely Advance my career.
5.0
·Reviewed May 3, 2021
Nice course about tensorflow deployment techniques
5.0
·Reviewed Mar 23, 2020
Very clear, the pace is right, content is very interesting and classes are engaging. What else is to desire? :)
5.0
·Reviewed Dec 1, 2020
If you want to learn extra libraries of tensorflow then take this
5.0
·Reviewed Apr 11, 2020
Fantastic course, very recomendable for advanced TensorFlow applications!!!
4.0
·Reviewed Jan 21, 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.
5.0
·Reviewed 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.
5.0
·Reviewed May 2, 2020
Very practical and advanced topics taught in easily understandable way.
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S
seyed
5.0
·Reviewed 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.
M
Michael
5.0
·Reviewed 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.
S
Sayak
5.0
·Reviewed 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.
M
Martín
5.0
·Reviewed 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!
M
Moustafa
5.0
·Reviewed Jul 5, 2020
great course for utilities to enhance the training and deployment experience
S
Suresh
4.0
·Reviewed 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
P
Pavel
3.0
·Reviewed 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.
V
Victor
2.0
·Reviewed 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.
O
Oussama
1.0
·Reviewed Apr 3, 2020
DIsapointed..
J
Juan
5.0
·Reviewed 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.
R
Rick
5.0
·Reviewed 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.
A
AKSHAY
5.0
·Reviewed 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.
O
Okta
5.0
·Reviewed 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.
K
Krzysztof
5.0
·Reviewed 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
R
Rohit
5.0
·Reviewed 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.
D
Dave
5.0
·Reviewed 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.
J
Jiten
5.0
·Reviewed Nov 10, 2021
Grader messages are not helpful due to which debugging time increases. Rest the course is quite informational and useful.
E
Ernesto
5.0
·Reviewed Mar 24, 2020
Very clear, the pace is right, content is very interesting and classes are engaging. What else is to desire? :)
N
Nur
5.0
·Reviewed 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.
A
Adrian
5.0
·Reviewed Mar 8, 2020
ver good course to get first insights for orientation and later deep dives. I like it very much!