This repository contains my end-to-end Machine Learning pipeline to predict the health status of trees based on environmental data.
Rather than relying solely on high-level APIs, I focused on implementing fundamental algorithms from scratch to deeply understand the underlying mathematics and optimization.
visualisation-des-donnees(2).ipynb: Data exploration, feature engineering, and handling imbalanced datasets.knn-program-final(2).ipynb: Manual implementation of the K-Nearest Neighbors algorithm.baies-naif-final(3).ipynb: Naïve Bayes implementation from scratch with mathematical Laplace smoothing.les-arbres-de-d-cisions-final(1).ipynb: Random Forests and Decision Trees.
Built by a 2nd-year Math & CS Double Major student.