Course Project for UCSD ECE143: Programming for Data Analytics
-
Updated
Dec 8, 2022 - Jupyter Notebook
Course Project for UCSD ECE143: Programming for Data Analytics
This repository contains code for predicting the price of mobile phones using regression models. It includes the implementation of various regression techniques such as Random Forest Regression, Decision Tree Regressor, Linear Regression, and Lasso Regression.
Our Economic Forecasting Model leverages Genetic Algorithms and Random Forests to provide farmers, policymakers, and businesses with cutting-edge insights for informed, profitable decisions in the ever-changing world of agriculture.
An explainable inductive learning model on gene regulatory and toxicogenomic knowledge graph (under development...)
This repository contains code for predicting the price of mobile phones using regression models. It includes the implementation of various regression techniques such as Random Forest Regression, Decision Tree Regressor, Linear Regression, and Lasso Regression.
Uses machine learning to analyze e-commerce data, uncover insights, and offer actionable suggestions
Supporting code for https://www.biorxiv.org/content/10.1101/796714v4
Trabajo de Fin de Grado del Grado de Ingeniería Informática, realizado en la Escuela Técnica Superior de Ingeniería Informática de la Universidad Politécnica de Madrid.
Recurrent Dynamic Graph Mapper using GNN
This project aims to analyze trends in the Paycheck Protection Program and to generate predictive models based on demographics to predict the likelihood of receiving a loan.
In this project, I utilize the Insurance US dataset to predict health insurance costs based on various input features, enabling insights into the factors influencing insurance charges.
Application of predictive models on a real data set of the obstetric medicine field and methods of interpretability on the previously fitted XGBoost model.
This repo guides you to to build predictive models of Titanic survival, including data-viz & pre-processing, feature analysis, building predictive models and performance evaluation.
Timeseries data analysis and forecasting using Python
Mobile Air Quality Monitoring System (MAQMS) - An IoT Network of Air Quality Monitoring stations connectes to Azure cloud to provide insights and predictive models of air quality in Mexico City.
Predictive Modeling Project for League of Legends Dataset
Implementation of timeseries predictive models with public transport data.
Mix of good tools for portfolio analysis
Statistical analysis of animal shelter intakes and outcomes from Dallas Animal Services, and a fullstack app for predicting animal outcomes based on intake variables.
A few-shot learning approach to forecasting the evolution of the brain connectome.
Add a description, image, and links to the predictive-models topic page so that developers can more easily learn about it.
To associate your repository with the predictive-models topic, visit your repo's landing page and select "manage topics."