Install the toolkit for the subject, and submit a report on the process, including the

following critical components

a$)$ Ubuntu $22\mathrm{.}04$

b$)$ Anaconda$3$

c$)$ python $=3\mathrm{.}10$

d$)$ pytorch $=2\mathrm{.}2\mathrm{.}0$

e$)$ oneccl bind $pt=2\mathrm{.}2\mathrm{.}0$

f$)$ torchvision $=0\mathrm{.}17\mathrm{.}0$

g$)$ torchaudio $=2\mathrm{.}2\mathrm{.}0$

h$)$ deepspeed $=0\mathrm{.}14\mathrm{.}0$

i$)$ Intel OneAPI toolkit $($Al Tools for Deep Learning, Al Tools for Classical Machine

Learning, and Al Tools for Data Analytics$),$ including:

$(1)$ intel$-$extension$-$for$-$tensorflow $=2\mathrm{.}15$

$(2)$ intel$-$extension$-$for$-$pytorch $=2\mathrm{.}2\mathrm{.}0$

$(3)/$intel$-$extension$-$for$-$scikit$-$lear

j$)$ modin$-$all $=0\mathrm{.}26\mathrm{.}1$

k$)$ xaboost

I$)$ scikit$-$learn$-$intelex

m$)$ Jupyter Notebooks, Matplotlib, Seaborn, Pandas, Scikit$-$learn

Using the installed toolkit, classify the Survive data using KNN

a$)$ Train the KNN using fit$()$ function

b$)$ Predict the following examples using the trained KNN$.$

$(13,20)$;$(20,15)$;$(25,20)$;$(20,40)$