scikit-learn

Training various machine learning models for NFLX stock price prediction with data collection, cleaning, and visualization tools.

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

examples of Applied ML

La junta directiva de la cadena de supermercados Universal Food ha observado una estabilización en sus ventas y busca comprender cómo mejorar la relación con sus clientes, entendiendo sus hábitos de compra, para ofrecerles un servicio de mayor calidad. El objetivo es proporcionarles una experiencia de compra más personalizada, rápida y efectiva.

Code and data for Natural Language Processing in Action, 2nd Edition, by Maria Dyshel and Hobson Lane for Manning Publications

Project Repository for the MLDS Course

Code used to process the recorded data

this project it to practice all concepts and knowledge in the course mlops-zoomcamp

PI de la Carrera de Ingeniería en Computación 2021 - FCEFyN (UNC)

This is a Collaborative-Based Product Recommendation Engine which recommends most correlated products to the Customer based on the Ratings patterns of other customers who bought that same product also.

Exploit scikit-learn to predict insolvency on Detroit's house-maintenance penalties

Protein-Protein Docking Scoring function.