I’ve tried lesson 1 code with 3 classes, so i have 3 folders. I have not really changed the code from lesson 1, it appears to run, although accuracy is not great. As asked above, how to we read the prediction as it seems to still score between 0 and 1. For 2 classes, closer to zero is first class, and closer to 1 is second class, but how to read this 0-1 score with 3 classes ?

In the following lessons those concepts are explained in more detail. But basically for multiclass classification the Softmax function (or actually the log of it) is used. Softmax gives like the probability of each class (the values are between 0 and 1 and they sum to 1). So in numpy you call argmax() to find the class with highest probability. You need to do np.exp(preds) to get the actual probabilities since the predictions are the logarithm of softmax.