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.
Этот курс входит в специализацию ''Специализация TensorFlow: Data and Deployment'
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Об этом курсе
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have basic familiarity with building models in TensorFlow.
Чему вы научитесь
Use TensorFlow Serving to do inference over the web
Navigate TensorFlow Hub, a repository of models that you can use for transfer learning
Evaluate how your models work and share model metadata using TensorBoard
Explore federated learning and how to retrain deployed models while maintaining data privacy
Приобретаемые навыки
- TensorFlow Serving
- Machine Learning
- federated learning
- TensorFlow Hub
- TensorBoard
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have basic familiarity with building models in TensorFlow.
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Программа курса: что вы изучите
TensorFlow Extended
Sharing pre-trained models with TensorFlow Hub
Tensorboard: tools for model training
Federated Learning
Рецензии
- 5 stars81,44 %
- 4 stars14,25 %
- 3 stars2,94 %
- 2 stars0,90 %
- 1 star0,45 %
Лучшие отзывы о курсе ADVANCED DEPLOYMENT SCENARIOS WITH TENSORFLOW
Grader messages are not helpful due to which debugging time increases. Rest the course is quite informational and useful.
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.
Excellent Content. It Will definitely Advance my career.
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.
Специализация TensorFlow: Data and Deployment: общие сведения

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