Advanced Deployment Scenarios with TensorFlow
TensorFlow: Data and Deployment,
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.
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| Rating | 5.0★ based on 3 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 4-5 hours/week |
| Starts | Jul 3 (43 weeks ago) |
| Cost | $49 |
| From | deeplearning.ai via Coursera |
| Instructor | Laurence Moroney |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming |
| Tags | Computer Science Software Development Mobile And Web Development |
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commentary about common practicalities
Besides that, the courses have tons of commentary about common practicalities.
helpful like alexander ivanov
Plus people who are helpful like Alexander Ivanov.
rather than randomly reading
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.
features provided by tensorflow
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.
helped everyone especially for
Who helped everyone especially for the week 2 assignment.
understand stuff with readable
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.
also help others
I learned a lot and will use it to my best interest to also help others.
practicals well set
Enjoyed the course, the balance between the quiz and the practicals well set.
week 2 assignment
keep up
Keep up the good work and thanks for keeping the length of the videos short and concise.
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| Rating | 5.0★ based on 3 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 4-5 hours/week |
| Starts | Jul 3 (43 weeks ago) |
| Cost | $49 |
| From | deeplearning.ai via Coursera |
| Instructor | Laurence Moroney |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming |
| Tags | Computer Science Software Development Mobile And Web Development |
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