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Back to Device-based Models with TensorFlow Lite

Learner Reviews & Feedback for Device-based Models with TensorFlow Lite by DeepLearning.AI

565 ratings

About the Course

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. This second course teaches you how to run your machine learning models in mobile applications. You’ll learn how to prepare models for a lower-powered, battery-operated devices, then execute models on both Android and iOS platforms. Finally, you’ll explore how to deploy on embedded systems using TensorFlow on Raspberry Pi and microcontrollers. 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....

Top reviews


Mar 24, 2021

Great course - I learned a lot about how TensorFlow can be run on a wide variety of devices. I am especially interested in TensorFlow running on Raspberry Pi, Google Dev Board (Coral) and Jetson Nano.


Oct 12, 2020

Really informative course on tf lite for beginners like me, it has given serious thoughts about the EDGEML field and opportunities , thanks coursera and for this kind of courses.

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