$1-$ Define your problem.

$2-$ Collect your dataset.

a$.$ Describe the dataset in detail $($Explain each columns$)$

b$.$ Define your input features and the target columns.

$3-$ Provide clear visualizations of your dataset that help the viewers to understand the data.

$1)$ Apply the following data preparation process:

a$)$ Check for duplicated and missing values.

b$)$ Please conduct feature selection using correlation analysis and provide a corresponding figure. Subsequently, explain the figure in detail, highlighting which variables exhibit a strong association with the target variable, and provide a rationale for the same.

c$)$ Apply class imbalance for your data. This is only for those who have classification problems.

$2)$ Implement at least two machine learning algorithms and compare their results.

a$)$ For classification: illustrate the classification reports and discuss them.

b$)$ Implement Mean Square, Root Mean Square, and Mean Absolute Error for regression.