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Coursera Project Network による Optimize TensorFlow Models For Deployment with TensorRT の受講者のレビューおよびフィードバック

4.6
55件の評価
10件のレビュー

コースについて

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....

人気のレビュー

LS

2021年6月3日

Great workshop, all the concepts were very well explained.

AA

2022年3月14日

The first to introduce such a rare and important topic.

フィルター:

Optimize TensorFlow Models For Deployment with TensorRT: 1 - 10 / 10 レビュー

by Awais A

2021年3月28日

This is something that I was looking for. I've studied a lot of theories about TensorRT but this project gives a clear view of how to do it. Good job, and thanks for the awesome course.

One last thing, Please upload the TensorRT deployment of TensorFlow object detection on Jetson devices. That would be helpful

by Jorge G

2021年2月25日

I do not recommend taking this type of course, take one and pass it, however after a few days I have tried to review the material, and my surprise is that it asks me to pay again to be able to review the material. Of course coursera gives me a small discount for having already paid it previously. It is very easy to download the videos and difficult to get hold of the material, but with ingenuity it is possible. Then I recommend uploading them to YouTube and keeping them private for when they want to consult (they avoid legal problems and can share with friends), then they can request a refund.

by Luis S

2021年6月4日

G​reat workshop, all the concepts were very well explained.

by Abdelrahman A

2022年3月15日

T​he first to introduce such a rare and important topic.

by Fabian I M N

2021年4月20日

Excelent and compresed way of explaining TensorRT

by Nusrat I

2021年4月16日

Awesome project. Thank you so much.

by Chandra S

2020年12月13日

Excellent guided course

by ERNAZAROV B T O

2020年9月10日

Very good...

by Vignesh R

2021年7月8日

Need more theoretical explanation on concepts

by Yilber R

2020年10月1日

excellent