PORTFOLIO
Watch This! - Movie Recommender System
For my first Machine Learning project, along with Ezequiel L. Castaño I developed a Movie Recommender App using the Collaborative Filtering technique, in which users rate (like or dislike) different movies to train the algorithm to make them a movie recommendation. I studied the matrix factorization and dimensionality reduction algorithms Principal Component Analysis (PCA) and Singular Value Decomposition (SVD), and implemented an approximation of the SVD with Stochastic Mini-Batch L2-Regularized Gradient Descent and K-Folds Cross-Validation. The app was developed using Vue.js.
Monte Carlo Simulation Model for the Economic Impact of an Inventory-Dependent Business using s,S Inventory Policy
As a way of entering the field of Data Science, for my first project I developed, along with Ezequiel L. Castaño (see his post here), a Monte Carlo Simulation for a Business that manages its inventory with an s,S policy. The main goal was to make a basic simulation applying Monte Carlo Methods and analyzing it with basic statistical tools such as the sample mean, the variance, and confidence intervals. Moreover, the project was presented at the National Informatics and System Engineering Congress 2020 (CoNaIISI).