Just because something doesn’t do what you planned it to do doesn’t mean it’s useless.—Thomas Edison
To solve a particular problem, we try multiple solutions, and many times after a few iterations, we find the best solution. Machine learning and Deep Learning are no different. During the discovery phase, improvements and constant modifications are done to improve the performance of the previous version of the algorithms. The weakness observed in the last phase, the slowness in the computation, the incorrect classifications made – all pave the way for a better ...
