#3 Plot Figure 3.7 from PRML using your preferable language. Use line of intercept = -0.3 and slope =0.5 with gaussian noise (mean =0; var = 0.04) to generate 10 sample points (x_i, y_i) between -1 and +1 on x axis. For more details refer respective video lecture and PRML. Hint: You can define 2 dimensional grid uniformly between -1 and +1 on x-aix and y-axis respectively. Then calculate the probability of Gaussian for given mean and variance using library functions. Calculate the un-normalized posterior by multiplying (one-to-one) prior and likelihood grids; hence results in the same dimensional grid with posterior probability. Use heat map to plot the figure. Prior is gaussian distribution with mean = 0 and var = 0.5.
#1 1 . Ploting a graph using Gaussian Distribution for mean =5 and variance = 1 .
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Likelihood function for mean between 1 - 10 and keeping variance =1 constant for all.
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Plotting the best line which fits the given dataset using maximum likelihood function .