Create an XOR gate neural network using Python with the following information. Please provide both the code and graphs :$)$

x$1=\{0\mathrm{.}1,0\mathrm{.}9,0\mathrm{.}1,0\mathrm{.}9\}$ x$2=\{0\mathrm{.}1,0\mathrm{.}1,0\mathrm{.}9,0\mathrm{.}9\}$ x$3=\{1,1,1,1\}$ t $=\{0\mathrm{.}1,0\mathrm{.}9,0\mathrm{.}9,0\mathrm{.}1\}$

Stop the program when error is $<=($less than or equal to$)0\mathrm{.}1$

Learning rate is $0\mathrm{.}1($n $=0\mathrm{.}1)$

Simulate this in both online and offline learning and showcase the following graphs. There should be $4$ graphs in total!

$-$Online and offline for: error vs time

$-$Online and offline for: weights vs time

Thank you in advance!