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Avis et commentaires pour d'étudiants pour Advanced Deployment Scenarios with TensorFlow par

40 évaluations
8 avis

À propos du cours

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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1 - 7 sur 7 Avis pour Advanced Deployment Scenarios with TensorFlow

par 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.

par Michael

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.

par Sayak P

Feb 13, 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.

par Ernesto C

Mar 24, 2020

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

par Adrian P S

Mar 08, 2020

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

par 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.

par Pavel K

Mar 05, 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.