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Volver a Traffic Sign Classification Using Deep Learning in Python/Keras

Opiniones y comentarios de aprendices correspondientes a Traffic Sign Classification Using Deep Learning in Python/Keras por parte de Coursera Project Network

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Acerca del Curso

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....

Principales reseñas

NB

20 de jun. de 2020

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

21 de may. de 2020

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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51 - 52 de 52 revisiones para Traffic Sign Classification Using Deep Learning in Python/Keras

por KUNAL S

26 de ago. de 2020

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.

por raghu r m

10 de may. de 2020

not completely explaining the methods being used.