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Showing posts from June, 2019

Gradient Descent is decent!

     * For best experience open the blog in Desktop-mode*       OBJECTIVE: To find the best fit line.       CLAIM: When the Loss Function is minimized, we obtain the best fit line.        Well, here we go. In Machine learning( ML ),finding the optimal solution for the given set of data points is a very essential step. Gradient Descent plays an important role in doing so with the help of statistical analysis. There are 3 types of Gradient descents, Batch Gradient Descent Stochastic Gradient Descent Mini-batch Gradient Descent       Here we will see how Gradient Descent works overall. Considering a Linear regression let us operate on the graph shown below,      The 'x' shown represent the data points whereas the line passing through those points represents the solution. Current solution may or may not be optimal since the difference between ACTUAL POINTS and PR...