Popular GitHub Repositories for Lasso

H2Oai GPU Edition

Sparse and structured neural attention mechanisms

Machine learning algorithms in Dart programming language

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks

This repository is dedicated to the machine learning analysis on StockX prices. Blog ?

A Machine Learning project for Machine Learning Internship offered by InternshipStudio.

Regularization Paths for Huber Loss Regression and Quantile Regression Penalized by Lasso or Elastic-Net

In this project I have performed analysis and prediction on 1,3,and 5 year returns on 1064 mutual funds in India. I have scraped data from a website which is the most visited website for mutual fund investments.I have tested regression models linear model,SGD Regressor , Random Forest Regressor,Decision Tree Regressor,Ridge,MLP Regressor and linear model (Lasso).After which I have selected the best perorming model and performed Hyper parameter tuning and then deployed an interactive application which can generate the visualization and send an email with the visualization to the users email address.

A Python library for sGMRFmix model for anomaly detection in time series

Fast Sparse Linear Models for Big Data with SAGA

Automatic hyperparameter selection for Lasso-like models solving the M/EEG source localization problem

End-to-end machine learning project for diamond price prediction using Lasso Regression with 93% accuracy.

The project aims to design machine learning algorithm which is able to predict energy densities of supercapacitors by using input data that is enriched from the results came from image processing techniques.

focus on machine learning techniques for clustering and regression analysis. It explores real-world datasets to solve challenges and extract meaningful insights. Specifically, it addresses the critical task of predicting when to replace broaches used in manufacturing airplane engines.

machine learning scala

This project explores ML techniques across classification and regression. It includes penguin species classification, breast cancer prediction, and baseball performance prediction using regularization. After, I will develop an XGBoost model for hotel cancellation prediction, analyzing key booking factors and optimizing performance. (In Progress)