Machine Learning, Data Science, Deep Learning, Artificial Intelligence, Regression.
np.random.rand(len(df)) < 0.8 train_x = xdata[msk] test_x = xdata[~msk] train_y = ydata[msk] test_y = ydata[~msk] # build the model using train set popt, pcov = curve_fit(sigmoid, train_x, train_y) # predict using test set y_hat = sigmoid(test_x, *popt) # evaluation print("Mean absolute error: