A python port of the glmnet package for fitting generalized linear models via penalized maximum likelihood.

MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3

Group elastic net implementation in PyTorch.

Predict the profitability of potential coffee shop locations using SQL and Python. Combines data engineering with feature-rich regression modeling, visual analytics, and business insights to support data-driven site selection and retail decision-making.

Analyze and predict daily productivity using SQL, machine learning, and psychology. This project combines behavioral data, circadian rhythm analysis, and ElasticNet regression to model focus, stress, and performance, transforming work patterns into actionable insights.

Repository for the Recommender Systems Challenge 2020/2021 @ PoliMi

OIKAN is a neuro-symbolic machine learning framework inspired by Kolmogorov-Arnold representation theorem. It combines the power of modern neural networks with techniques for extracting clear, interpretable symbolic formulas from data. OIKAN is designed to make machine learning models both accurate and Interpretable.

In this project, I applied different regression models for rmse and mae on antenna dataset for predict signal strength.

glmnet for python

Analysis of NBA player stats and salaries of the 2016-17 for the 17-18 season

Code for paper "面向物联网隐私数据分析的分布式弹性网络回归学习算法"

Applied Machine Learning

SaleFore AI: Ultra-accurate sales forecasting using ensemble ML (XGBoost, LightGBM, CatBoost) with RTX 4060 GPU optimization. Achieves 88-95% accuracy with advanced hyperparameter tuning.

Predicting the Residential Energy Usage across 113.6 million U.S. households using Machine Learning Algorithms (Regression and Ensemble)

Solution Paths of Sparse Linear Support Vector Machine with Lasso or ELastic-Net Regularization

📈 Stock Price Prediction using ElasticNetCV | 🥈 Dacon Top 5%

Using publicly available data for the national factors that impact supply and demand of homes in US, build a data science model to study the effect of these variables on home prices.

A repository containing the code for a machine learning project about predicting the outcome of soccer matches, including a simple web application built with Flask.

The objective of the competition was to create the best recommender system for a book recommendation service by providing 10 recommended books to each user. The evaluation metric was MAP@10.

Model that uses 10 different algorithms to predict the revenue of a movie before it's release

Nested Cross-Validation for Bayesian Optimized Linear Regularization

Final project for the 2019 Colombia Data Science for All (DS4A) program.

Team TwinAI repo for Challenge 1 of the Oracle FormulaAI Hack 2022. Our team emerged as one of the 9 prize-winning teams and won the Newcomer Team award.

Bu proje, Kontr firmasının borsa verilerini kullanarak hisse senedi fiyatlarının gelecekteki değerlerini tahmin etmeye yönelik gelişmiş makine öğrenimi modelleri içerir. Farklı algoritmalarla performans analizi yaparak yatırım kararlarını destekleyici öngörüler sağlar.

This repository contains code for training an ElasticNet regression model using MLflow. The model predicts the quality of wine based on various features.

Data Science Capstone Project Using NLP to classify articles as Bullish/Bearish and or Important.

A machine learning application aimed at predicting employee salaries based on various features such as experience, education level, location, etc. By using different models and techniques, the project seeks to present an optimized model for salary predictions.

Predicting house price

Predict the quality of red wines using linear models.

Objective: Predicting whether the customer will return or not in the next month. Techniques used: XGBoost, logistic regression, attention based LSTM neural network, self attention based transformer neural network