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Traffic Sign Classification Using Deep Learning in Python/Keras(으)로 돌아가기

Coursera Project Network의 Traffic Sign Classification Using Deep Learning in Python/Keras 학습자 리뷰 및 피드백

4.6
별점
353개의 평가
52개의 리뷰

강좌 소개

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....

최상위 리뷰

NB

2020년 6월 20일

Very nice course, everything was explained perfectly.

Can 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

2020년 5월 21일

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.

필터링 기준:

Traffic Sign Classification Using Deep Learning in Python/Keras의 52개 리뷰 중 51~52

교육 기관: KUNAL S

2020년 8월 26일

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.

교육 기관: raghu r m

2020년 5월 10일

not completely explaining the methods being used.