a$)$ Data analyst observed that pre$-$processing phase before the model training, wasn't able to

capture the influential attributes of the data. During the model training, analyst finds a trick

to regularize the model being trained from overlearning pattern from such un$-$influential

attributes. What technique might have been found by the analyst? Justify your answer with

any plagiarism free example.

$[2$ marks$]$

b$)$ What are the three components $>[2*2=4$ marks $]$ : Performance, $T$: Task, $E$: Experience $>of$ each $of$ the

below machine learning problem? Identify the type $of$ machine learning required for below

cases based $on$ the level $of$ supervision. Justify your answer with $no$ more than $30$ words

and sample feature design.

$[2*2=4$ marks $]$

idat analyst observed the pre$-$processing phase before the model training, wasnt able to capture the influential attributes of the data. during the modwl training