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Learner Reviews & Feedback for Optimize TensorFlow Models For Deployment with TensorRT by Coursera Project Network

4.7
stars
10 ratings
2 reviews

About the Course

This is a hands-on, guided project on optimizing your TensorFlow models for inference with NVIDIA's TensorRT. By the end of this 1.5 hour long project, you will be able to optimize Tensorflow models using the TensorFlow integration of NVIDIA's TensorRT (TF-TRT), use TF-TRT to optimize several deep learning models at FP32, FP16, and INT8 precision, and observe how tuning TF-TRT parameters affects performance and inference throughput. Prerequisites: In order to successfully complete this project, you should be competent in Python programming, understand deep learning and what inference is, and have experience building deep learning models in TensorFlow and its Keras API. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....
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1 - 2 of 2 Reviews for Optimize TensorFlow Models For Deployment with TensorRT

By ERNAZAROV B T O

Sep 10, 2020

Very good...

By Yilber R

Oct 01, 2020

excellent