The project FIRST PROJECT_MACHINE LEARNING_AWESOME BANK was my final project from my Post Graduate Degree in Data Science's Unit of Study Machine Learning Fundamentals. I got a grade of 19 in 20 on this project, finalizing also the Unit of Study Machine Learning Fundamentals with a final grade of 19 in 20. The project that I present here incorporates some improvements pointed out by the Professor.
This project is about the following business problem (Kaggle's challenge):
"After your success in the first project at The Awesome Bank, an even more exciting new project appears!
The marketing team wants to launch a new campaign aimed at convincing customers to open term deposits.
Until now, the strategy was to call as many people as possible, indiscriminately, and try to sell them the product. However, this approach, in addition to spending more resources because it involves having several people calling all customers, is also uncomfortable for some customers who do not like to be disturbed by this type of call. After the calculations, it was concluded that:
- For each customer identified as a good candidate, and is the target of the campaign but does not adhere to the term deposit, the bank has a cost of 500 euros.
- For each customer who is identified as a candidate, and as such is not the target of the campaign but was actually a good candidate and would join, the bank has a cost of 2000 euros.
The goal of this project was to based on this information, help the marketing team by creating a model that selects the best candidates to be targeted by the campaign, in order to reduce costs."
In this repository, I also added two more projects named - Machine-Learning_group-project and Exploratory-Data-Analysis_first-project - where I share a little more of my skills as a data scientist, the project Machine-Learning_group-project was developed with two more colleagues from my course.
Machine-Learning_group-projectfocused on feature engineering mostly, manipulating in json.Exploratory-Data-Analysis_first-project- focused mostly on data visualization and exploratory data analysis.
I must thank my professors and my colleagues who helped me so much in my evolution as a problem-thinker, which contributed so much to the development of this project and its success, as my first machine learning project.