Machine Learning, Data Science, Deep Learning, Artificial Intelligence, Regression.
for our model. Lets first normalize our x and y: How we find the best parameters for our fit line? we can use curve_fit which uses non-linear least squares to fit our sigmoid function, to data. Optimal values for the parameters so that the sum of the squared residuals of sigmoid(xdata, *popt) -