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Updated in [August 31st, 2023]

What does this course tell?
(Please note that the following overview content is from Alison)
This Specialization will teach you how to effectively deploy machine learning models in the real world. You'll explore four different scenarios, including TensorFlow Serving, TensorFlow Hub, TensorBoard, and Federated Learning. You'll also learn how to use data to train models, evaluate models, and share model metadata. If you are new to TensorFlow, we recommend taking the TensorFlow in Practice Specialization first, and the Deep Learning Specialization for a deeper understanding of neural networks.

We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
By taking this course, learners will acquire advanced skills and knowledge in deploying machine learning models with TensorFlow. They will learn how to use TensorFlow Serving to do inference over the web, use TensorFlow Hub to access a repository of models for transfer learning, use TensorBoard to evaluate and understand how models work, and explore federated learning to retrain deployed models with user data while maintaining data privacy. Additionally, learners will gain a deeper foundational understanding of how neural networks work.
lHow does this course contribute to professional growth?
This Specialization in Advanced Deployment Scenarios with TensorFlow provides professionals with the knowledge and skills to effectively navigate various deployment scenarios and use data more effectively to train models. Through this course, professionals will gain an understanding of TensorFlow Serving, TensorFlow Hub, TensorBoard, and federated learning, and how to use these technologies to deploy models in the real world. This course will help professionals to develop a deeper foundational understanding of how neural networks work, and will provide them with the skills to effectively use TensorFlow to deploy models in the real world.

Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education. It provides an in-depth exploration of four different deployment scenarios for machine learning models, as well as introducing learners to TensorFlow Serving, TensorFlow Hub, TensorBoard, and federated learning. It builds upon the TensorFlow in Practice Specialization and provides a deeper foundational understanding of how neural networks work.