Laurence Moroney
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. deeplearning.ai is Andrew Ng’s new venture which amongst others, strives for providing comprehensive AI education beyond borders.
Instructor Details
Courses : 8
Specification: Advanced Deployment Scenarios with TensorFlow
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5 reviews for Advanced Deployment Scenarios with TensorFlow
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| Price | Free |
|---|---|
| Provider | |
| Duration | 9 hours |
| Year | 2020 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
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Sayak P –
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.
seyed r m –
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.
Michael –
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.
Ernesto C –
Very clear, the pace is right, content is very interesting and classes are engaging. What else is to desire? 🙂
Chun Y Y –
Many useful stuffs if you want to move for Tensorflow or AI Deployment