Machine Learning Hypothesis function Cost function and Gradient Descent Algorithm Short Notes
This is a short scrap notes from the Machine Learning Course taught by Associate Professor, Andrew Ng, Stanford University on Coursera. hypothesis = hØ(x) + Øo + Ø1X Parameters = Øo , Ø1 Our Goal = minimise Ø0 , Ø1 that is the cost function J(Ø0, Ø1) GRADIENT Descent. An algorithm wich minimises the…