Use python based APIs and perform the Regression of activities by dataset

Regression

Any of the Linear Regression $($any of Gradient $/$ Stochastic $/$ MiniBatch$)/$linear basis models$/$KNN$/$Locally weighted regression$/$ any of the regularization techniques$).$

Justify your design choices at each step: Write as a markdown cell in jupyter notebook at the beginning of each subsection

$1.$ Perform and explain necessary pre$-$processing $/$ feature engineering on this dataset $[0\mathrm{.}5]$

$2.$ Perform the Machine Learning activity. Explain Attributes of interest, Regularization type with reason, model selected with reason $[1\mathrm{.}5]$

$3.$ Quantify and explain the quality of your ML model. Explain the choice of evaluation metric $[1\mathrm{.}5]$

$4.$ Your observation about the results $($Hint: comment on the problem statement and conclude the effectiveness of the machine learning activity$)[0\mathrm{.}5]$