Machine Learning, Optimization, Random Walk, Data Science, Gradient Descent.
this is done a new random direction is chosen and we start the process from 1 again. If at 2 a random direction cannot be found that decreases the cost function then we must be at a minimum and so exit the algorithm and return our coordinates in intercept-gradient space [4]. It is this random