MACHINE LEARNING QUESTION, USE JUPYTER LAB, NO AI PLZ:

import this:

import sys

from packaging import version

import sklearn

import matplotlib.pyplot as plt

import numpy as np

from sklearn.preprocessing import add$\_$dummy$\_$feature

import numpy as np

from sklearn import metrics #Import scikit$-$learn metrics module for accuracy calculation

from sklearn.model$\_$selection import train$\_$test$\_$split

from sklearn.metrics import confusion$\_$matrix, ConfusionMatrixDisplay

from sklearn.datasets import make$\_$blobs

print$("$Sklearn package",sys$.$version$\_$info$)$

print$("$Sklearn package",sklearn.$\_\_$version$\_\_)$

assert sys$.$version$\_$info $>=(3,10)$

#assert version.parse$($sklearn$.\_\_$version$\_\_)>=$ version.parse$("1\mathrm{.}2\mathrm{.}1")$

plt$.$rc$(\text{'}$font$\text{'},$ size$=12)$

plt$.$rc$(\text{'}$axes$\text{'},$ labelsize$=14,$ titlesize$=14)$

plt$.$rc$(\text{'}$legend$\text{'},$ fontsize$=14)$

plt$.$rc$(\text{'}$xtick$\text{'},$ labelsize$=10)$

plt$.$rc$(\text{'}$ytick$\text{'},$ labelsize$=10)$

$-----$

Questions:

# Q$1$ Gradient Descent

## Write a gradient descent method that finds the minimum for this function:

$f$($x$)=3$x$^2+5$x$

$-----$

def f$($x$)$:

return$(3*$x$*$x $+5*$x$)$

X $=$ np$.$linspace$(-10,10,1000)$

y $=[$f$($x$)$ for x in X$]$

plt$.$figure$($figsize$=(7,4))$

plt$.$plot$($X$,$ y$,$ linewidth$=2)$

plt$.$xlabel$($r$"$$x$$")$

plt$.$ylabel$($r$"$$f$\backslash ($x$)$$$")$

plt$.$grid$()$

plt$.$show$()$

## Plot f$($x$)$ vs iteration

## Use these initial parameters

eta $=0\mathrm{.}2$ # learning rate

n$\_$epochs $=50$

theta $=10$