Added gradient descent

Author: anesh612

algorithms/machine_learning/Gradient-Descent/gradientdescent.m

@@ -0,0 +1,27 @@
+% This function demonstrates gradient descent in case of linear regression with one variable.
+
+% Theta is a column vector with two elements which this function returns after modifying it.
+
+% This function receives the feature vector x, vector of actual target variables Y, Theta
+
+% containing initial values of theta_0 and theta_1, learning rate Alpha, number of iterations
+
+% noi.
+
+function Theta = gradientdescent(x, Y, Theta, Alpha, noi)
+
+    n = length(Y); % Number of training examples. 
+
+    for i = 1:noi 
+
+        theta_1 = Theta(1) - Alpha * (1 / n) * sum(((x * Theta) - Y) .* x(:, 1)); % Temporary variable to simultaneously update theta_0 but i have used 1 to avoid confusion since indexing in MATLAB/Octave starts from 1.
+    
+        theta_2 = Theta(2) - Alpha * (1 / n) * sum(((x * Theta) - Y) .* x(:, 2)); % Temporary variable to simultaneously update theta_1.
+
+        Theta(1) = theta_1; % Assigning first temporary value to update first actual value simultaneously.  
+    
+        Theta(2) = theta_2; % Assigning second temporary value to update second actual value simultaneously. 
+
+    end
+
+end