Gradient-based optimization

See section 4.3 Gradient-Based Optimization (pages 79 to 83) in “Goodfellow, I., Bengio, Y., Courville, A. (2016). Deep Learning. United Kingdom: MIT Press.” Then:

• Pick a nonlinear function f(x) of your own choice to minimize that on some interval (a,b) has a minimum.
• Pick epsilon of your own choice for the learning rate and the staring input x in (a,b).
• For the submission provide in the plain text:function, interval, epsilon, and starting point you picked.5 consecutive x values that are updated using gradient descent procedure.calculations for the 5 consecutive x values.

Make sure that the ‘SafeAssign’ score is below 30%. You can change the function and input names