Software Developer |
Business Analyst |
Aspiring Data Scientist /
ML Engineer / AI Developer
Hi 👋🏼, I'm Kevin Milli, a Data Analyst and banking consultant since November 4th, 2024. After completing over 3500 hours of training in Data Science and AI, I specialized in data analysis and machine learning model development. I'm aiming for roles such as Data Scientist, ML Engineer, or AI Developer. I approach every challenge with both an analytical mindset and a creative spirit. Outside the tech world, I compose music, travel, and stay active through sports.
Decision Tree algorithm: In this project, I implemented the Decision Tree algorithm, one of the most powerful machine learning algorithms that maintains readability and facilitates easy interpretation of data.
Customer Analysis and Segmentation: During this project, I learned various aspects of how to classify a customer and what measures can be taken in the case of churn.
Ames housing predictions: In this project, I successfully applied several regression algorithms with the aim of predicting the market price of a property based on some of its intrinsic features (number of rooms, square footage, etc.).
USA Investigation - Exploratory Data Analysis: I am very proud of this investigation on the United States. The research was initially focused on whether the American armed forces had racial biases. However, during the investigation, the research took another direction.
File organizer: This code aims to organize the specified folder by dividing the various types of data into subfolders to keep everything tidy.
Final capstone project on Coursera: An incredible journey to discover Space-X, from data collection, through the creation of a model to determine the outcome of a launch, and finally, the creation of a dashboard to report the most important data.
Heart attack prediction: The application of artificial intelligence in the medical field is unparalleled. The ability to predict a heart attack will save many lives.
Water potability prediction: In this notebook, I conduct an investigation on drinking water. In this work, I had the opportunity to develop and use an algorithm to compare two distributions, proving to be very useful for the analysis.
Snake Game: I wanted to try replicating the iconic Snake game. To develop the game, I used Python and the turtle library. Do you still remember how to play?