Traffic Sign Classification Using Deep Learning in Python/Keras
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.
Artificial Intelligence (AI)
由 AI 提供Aug 12, 2020
Pretty cool idea and made it easy to walk through to code
由 SS 提供Apr 10, 2020
Thank you so much for such an awesome course ryan ahmad sir. I got 100/100 from your teaching. I wish i could meet you personally.
由 MK 提供Nov 8, 2020
Course was really good but it can have some more stuff like using model in a web app
由 GG 提供May 16, 2020
the instructor explains very well each and every line of code.