Andrew Ng's Convolutional Neural Networks course on Coursera, part of the Deep Learning Specialization, covers building CNNs for image data, including convolution, pooling, and architectures used in computer vision.

Commenters point to it as the specialised follow-up to Andrew Ng's ML course for learning convolutional neural networks.

On Reddit (2)

1. Recommendsxwrdr/learnmachinelearning2018in “Object detection: Is ML the right tool for this job?”▲ 2

   Here some code for the OpenCV part (not tested, you might need to fix some minor things): img = cv2.imread(filename) b,g,r = cv2.split(img) # apply Gray World Ba, Ga, Ra = np.mean(b), np.mean(g), np.mean(r) K = (Ba + Ga + Ra)/3. Bk, Gk, Rk = K/Ba, K/Ga, K/Ra b = np.array(b).astype(np.float64) b *=…

2. Recommendsvisargar/learnmachinelearning2018in “Where to start in learning ML?”

   After Andrew's ML course try a course on neural nets, or a specialised course on convolutional neural nets. There's such a course from Andrew as well.

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