In this video, I am trying to show how a single neurone with a linear activation function fails to classify the given data set. When I switch to a sigmoid activation function there was an improvement in classification but still not acceptable.

Then I added another hidden layer this resulted in a better classification still there needs to be a lot of improvement.

Finally, I increase the number of neurons in the hidden layer and this time I got all the data points classified correctly.