scikit-learn

Statistics for sci-kit learn.

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.

Introduction to classification using machine learning and deep learning (PyTorch, TensorFlow, Keras)

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

Relief algorithms implementation

Project Repository for the MLDS Course

Polynomial Regression Model single feature and multiple features using scikit-learn. check this project article on medium: https://medium.com/@alhendyrenad/build-a-polynomial-regression-model-in-python-using-scikit-learn-1b5fd31beb02

building a linear regression model using scikit learn.

Code used to process the recorded data

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

Basic exercises using the scikit-learn library

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.