This project describes a bank that offers services to private customers. The services provided by the bank include account management, loan sanctioning, etc. The bank wants to improve its services. For example, bank managers have only a vague idea who is a good customer (whom to offer some additional services to) and who is a bad customer (whom to watch carefully to minimize the bank's losses). Fortunately, the bank stores data about its customers, accounts (transactions over several months), loans already granted, credit cards issued. So bank managers hope to find some answers (and questions too) by analyzing this data.
Solve comand: By opening the comand prompt in this directory you can show the solution of each exercise via a specific comand.
"python main.py -s exercise-name" -> generic comand to show/execute the solution of a specific exercise
Help comand: You can also get some information about the exercise with the comand:
"python main.py -h exercise-name" -> It will show the name and the task of the exercise
Available exercises names: These are the names to insert in the field exercise-name for both solve and help comands
Note: By running "python main.py -h" all these names will be shown
ch1-ex1 -> clean the database ch1-ex2 -> define a problem to improve the bank's services ch1-ex3 -> Show how Machine Learning can be used to solve this problem
ch2-ex1 -> Predict the average amount of money for an account ch2-ex2-l1 -> Show which clients have credit cards ch2-ex2-l2 -> Show which clients asked the bank for loans ch2-ex2-l3 -> Show which clients are minors ch2-ex2-l4 -> Show, for each sex, the number of clients ch2-ex2-l5 -> Show the types of credit cards the bank offers