Why would the value of x never cross 5 irrespective of number of times the loop is increased.
x=0;
error=[]
lr = 0.1
plt.plot(X,Y)
for i in range(100):
gradient = 2*(x-5)
x = x - lr*gradient
print(x)
err = (x-5)**2
error.append(err)
plt.scatter(x,err)
hey @indrabijaynarayan ,
Just imagine you are playing a game in which you have climb stairs only , but after some particular intervals , step size decreases but you speed remains the same ( there is no change in your speed ) , after another interval step size is reduced again, and again and again.
a time comes when these step sizes become really small , almost negligible, but the game keeps on moving.
Similarly , it is working here. Your goal is to reach as close as possible to your stated value 5. But your learning rate says , you keep trying buddy , i will not let you reach 5 , but i can help you reach very much closer to it , such that 5 will be just adjacent to you.
So as you move forward and calculate error , initially its value is big ,so you take big steps even lowering it by multiplying it by learning rate. But after some time , we observe error becomes very less and hence change in value of x is also less. Error keeps on decreasing , decreasing ,decreasing …but never increases. Means your steps are going to be even smaller as you move forward.
This is the reason you are not able to cross value 5 after hundreds of iterations also.
I hope this would have resolved your doubt.
I know this explanation was a kind of waste , you can refer to this link for better understanding.
Thank You and Happy Learning 
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