Make adjustments and enhancements to a Machine Learning Python Script

I have a Machine Learning Python script which I would like adjustments and enhancements done to. The code is meant to be a process to which i can use for many different types of models. Essentially it is a template to use where i can just import any dataset, identify what my targets and features are, choose what type of model and then the code is able to run from start to finish. This code is not finished so this project is to build upon the current script (attached) The backgound is that i have many CSVs for different projects that contains three groups/elements: - Information Columns (information that doesnt get usedin the Machine Learning Process i.e - non features and non targets data. - Target Columns: (I have multiple columns which could be used as targets in the ML process). I plan to create different models trying to predict different targets. - Feature Columns: A set of column that I want to potentially use as features. I have attached a sample dataset which has the following: Columns A to E are "Information" columns Columns F to V are possible target columns Columns W to LU are possible features (columns KF to LU are missing data at the moment FYI) The following work I would like completed to my current script is: Functions/code built that takes the input dataframe and does the following: Already in code but may need adjusting: - Pre processing steps (where i can input which column/s are information, target & features) - One hot encodes categorical data given features - Scales features (would like to choose different types eg. min/max) - Model Training Things to add: - Feature Selection (which are the most important features to use) - Train / Test split / cross validation and get the dataframe ready - Add KNN clustering as a third Model option (alongside Classifier and regression options). - HyperParameter tuning - Model Evaluation (show scores, errors, which model is best). RSME would be great - Bring back in "Information" columns to evaluate the predictions against the full orgiinal dataset - Then a function to deploy algorithms on new datasets for future predictions. Please ask any quesitions before we get started to save any trouble down the track. I would like clearly defined functions and elegant code with comments so that I can easily run the ML process myself and it can work with any initial data csv. Thanks and hope to speak soon! James