Steps involved in creating the Model

# Part 1: Data preprocessing
    Importing the libraries
    Importing the dataset
    Dealing with missing data
    Encoding categorical variables
    Splitting the dataset into train and test set
    Feature scaling

# Part 2: Building the model
    Logistic Regression Model and cross Validation

# Part 3: Randomized Search to find the best parameters 

# Part 4: Final Model