Machine Learning, Data Science, Optimization, Editors Pick, Thoughts And Theory.
steps_df['outcome'].max(): print(f'maximum found at iteration {i}') break print(x_t, y_t) This is the iterations on the original surface: The iteresting feature is that at iteration i=4 the code moved backward and then stopped, effectively finding the maximum. Conclusions To conclude, we saw how to