Traffic Sign Classification Using Deep Learning in Python/Keras に戻る
Coursera Project Network による Traffic Sign Classification Using Deep Learning in Python/Keras の受講者のレビューおよびフィードバック
353件の評価
コースについて
In this 1-hour long project-based course, you will be able to:
- Understand the theory and intuition behind Convolutional Neural Networks (CNNs).
- Import Key libraries, dataset and visualize images.
- Perform image normalization and convert from color-scaled to gray-scaled images.
- Build a Convolutional Neural Network using Keras with Tensorflow 2.0 as a backend.
- Compile and fit Deep Learning model to training data.
- Assess the performance of trained CNN and ensure its generalization using various KPIs.
- Improve network performance using regularization techniques such as dropout.
人気のレビュー
NB
2020年6月20日
Very nice course, everything was explained perfectly.\n\nCan also add about testing the trained model using external data, like if we want to give an input and perform prediction then how it is done.
FB
2020年5月21日
Instructor was efficient in delivering the knowledge and I understood it very well. The exercises were also great. Overall, my aim for taking this course had been accomplished.
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Traffic Sign Classification Using Deep Learning in Python/Keras： 51 - 52 / 52 レビュー
by KUNAL S
•2020年8月26日
There is no support on the discussion forums and the dataset is also wrong. Poorly designed and its all spoon fed. There is no use of wasting time on this. It is a useless course because you will not learn anything from it.
by raghu r m
•2020年5月10日
not completely explaining the methods being used.
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