Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

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

A python package for penalized generalized linear models that supports fitting and model selection for structured, adaptive and non-convex penalties.

TwitPersonality: Computing Personality Traits from Tweets using Word Embeddings and Supervised Learning

Implementation of Relaxed Lasso Algorithm for Linear Regression.

For quick search

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

Applied Machine Learning

Drop-in replacement of sklearn's Linear Regression with coefficients constraints

Use Ridge Regression and Lasso Regression in prostate cancer data

Evaluating multiple classifiers after SVM-RFE (Support Vector Machine-Recursive Feature Elimination)

Machine Learning Code Implementations in Python

TNO MPC Lab - MPyC - Secure Learning

Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.

This toolbox offers 7 machine learning methods for regression problems.

Predicting hospital costs using Linear Regression and using feature engineering to improve the model performance.

Forecasting the likelihood of a customer defaulting their auto loan using classification models

Boston Housing Analysis: This repo presents an in-depth analysis of the Boston Housing dataset using Linear, Lasso, and Ridge Regression models. It explores data, preprocesses features, visualizes relationships, and evaluates model performance.

Data Science Case Study

Implements Linear Models for Regression(Linear, Ridge, Lasso Regressions) and Classification(Logistic Regression) from scratch in Python