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					import numpy as np | 
				
			
			
		
	
		
			
				
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					import matplotlib.pyplot as plt | 
				
			
			
		
	
		
			
				
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					############################### | 
				
			
			
		
	
		
			
				
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					#Datos originales | 
				
			
			
		
	
		
			
				
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					############################### | 
				
			
			
		
	
		
			
				
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					X = 2 * np.random.rand(100, 1) | 
				
			
			
		
	
		
			
				
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					y = 4 + 3 * X + np.random.randn(100,1) | 
				
			
			
		
	
		
			
				
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					plt.plot(X,y,".") | 
				
			
			
		
	
		
			
				
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					############################### | 
				
			
			
		
	
		
			
				
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					X_b = np.c_[np.ones((100,1)), X] #Se agrega x0=1 para cada instancia | 
				
			
			
		
	
		
			
				
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					eta = 0.1 #Pasos | 
				
			
			
		
	
		
			
				
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					n_itera = 1000 | 
				
			
			
		
	
		
			
				
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					m=100 | 
				
			
			
		
	
		
			
				
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					theta = np.random.randn(2,1) #Inicialización aleatoria | 
				
			
			
		
	
		
			
				
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					for iteracion in range (n_itera): | 
				
			
			
		
	
		
			
				
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						gradiente = 2/m * X_b.T.dot(X_b.dot(theta)-y) | 
				
			
			
		
	
		
			
				
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						theta = theta - eta * gradiente | 
				
			
			
		
	
		
			
				
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					print(theta) |