I would like to understand the difference between Sigmoid Neuron and logistic regression. Both these model looks same. Any inputs please.
I think the difference in Sigmoid Neuron and Logistic Regression is in spirit (not much in implementation
We see Logistic Regression as a popular classical Machine learning binary classification technique.
When we talk about Sigmoid Neuron (basically that same logistic regression unit), it is in context of Neural network. A sigmoid neuron is like a building block for a deep learning network. So you can see a logistic regression (or sigmoid neuron) as one unit/one neuron in a Neural network.