cinarcy/semantic-recommender

# 🔍 Semantic Article RecommenderThis project offers a simple way to find articles that are similar in meaning. It uses advanced techniques like Hugging Face embeddings and FAISS for efficient searching. 🛠️

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Adittt17/job-salary

This project aims to predict job salaries based on candidate profiles using machine learning. By comparing Lasso Regression and XGBoost Regressor, the analysis shows that XGBoost performs better with an R² score of 0.9078.

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manasw13/Stock_Price_Forecasting_Investment_Analysis

This repository contains a comprehensive analysis of stock price forecasting and investment strategies using R. It features various statistical models and visualizations to help users understand market trends and make informed decisions. 🐙📊

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Andersoncrs/Prediccion-del-Precio-de-Vehiculos-Un-Enfoque-con-Regresion-Lineal-y-Regularizacion

Este proyecto tiene como objetivo predecir el precio de vehículos usados utilizando técnicas de regresión lineal y regularización Lasso. A través del análisis y procesamiento de datos, se construye un modelo predictivo preciso e interpretable basado en las características más relevantes de cada vehículo.

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TaniyaGoyat/Laptop_Price_Predictor

Predict laptop prices using ML algorithms like Random Forest, with an interactive Streamlit web app.

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JuliaAI/MLJLinearModels.jl

Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)

Language: Julia - Size: 590 KB - Last synced at: 24 days ago - Pushed at: 24 days ago - Stars: 82 - Forks: 13

SKT1803/black-friday-sales-prediction

Supervised Machine Learning Regression – Black Friday Sales Predictions

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khanhtran0111/Rain-prediction

Rain prediction using machine learning and deep learning

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varun-soni-ai/LaptopPricePredictionProject

Laptop Price Prediction with Regression Analysis and Exploratory Data Analysis (EDA)

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SuryaVamsi-P/Patient-Survival-Prediction-ICU-Mortality-Modeling-R

Predicts ICU patient survival using clinical and demographic features with logistic regression, decision trees, LASSO, and AIC-based model selection in R. Designed for healthcare decision-making with real-world medical insights drawn from 92K+ patient records.

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bips-hb/wflsa

Weighted Fused Lasso Signal Approximator (wFLSA)

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ostad-ai/Machine-Learning

This repository contains topics and codes related to Machine Learning and Data Science, especially in Python

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lukfd/city-of-austin-car-crash-ml-study

Machine Learning study on the City of Austin, Texas, car crash data set

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julian0112/Insurance-ML-Regression-Models

The project will be focused on using regression to predict the "charges" target values of an insurance dataset based on different features. To make this possible we are going to make four different regression models, those being: Linear Regression, Lasso Regression, Ridge Regression and Elastic Net,.

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0xMrMasry/Weather-Data-Regression-Analysis-Project

This project applies and compares 3 different regression algorithms on a Weather History dataset to predict temperature values. It demonstrates how different regression techniques perform on the same dataset, with visualizations to aid in understanding model behavior and performance.

Language: Python - Size: 2.19 MB - Last synced at: 22 days ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

DanteSc03/BroachAlign-Machine-Learning

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.

Language: R - Size: 20.7 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 2 - Forks: 0

therionakkad/House-Price-Prediction

A Machine Learning project that predicts California house prices using Linear Regression and Random Forest. It includes data preprocessing, feature engineering, visualizations, and model evaluation with hyperparameter tuning using GridSearchCV.

Language: Python - Size: 397 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

sanjushasuresh/PREDICTING-SOLAR-ENERGY-PRODUCTION

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marveng6/car-vibes-eda-88-97-

This project explores car data and improves a model's accuracy from 88% to 97%. The goal is to see how tweaks affect performance and uncover patterns that help boost accuracy.

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khetansarvesh/Tabular-Cross-Sectional-Modelling

Implementation of algorithms such as normal equations, gradient descent, stochastic gradient descent, lasso regularization and ridge regularization from scratch and done linear as well as polynomial regression analysis. Implementation of several classification algorithms from scratch i.e. not used any standard libraries like sklearn or tensorflow.

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gyrdym/ml_algo

Machine learning algorithms in Dart programming language

Language: Dart - Size: 9.49 MB - Last synced at: 27 days ago - Pushed at: about 2 months ago - Stars: 192 - Forks: 31

DataSpieler12345/python-for-ds-ml

My Python learning experience 📚🖥📳📴💻🖱✏

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MoMo790-m/car-vibes-eda-88-97-

This project explores car data and improves a model's accuracy from 88% to 97%. The goal is to see how tweaks affect performance and uncover patterns that help boost accuracy.

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TNO-MPC/mpyc.secure_learning

TNO PET Lab - secure Multi-Party Computation (MPC) - MPyC - Secure Learning

Language: Python - Size: 66.4 KB - Last synced at: about 1 month ago - Pushed at: about 3 years ago - Stars: 4 - Forks: 0

ncn-foreigners/nonprobsvy

An R package for modern methods for non-probability samples

Language: R - Size: 50.3 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 48 - Forks: 5

MoMo790-m/car-vibes-eda-88-97

This project explores car data and improves a model's accuracy from 88% to 97%. The goal is to see how tweaks affect performance and uncover patterns that help boost accuracy.

Language: Jupyter Notebook - Size: 460 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

temulenbd/dublin-parking-suspensions-analysis

PROJECT NAME: Exploration and analysis of publicly available data: suspension of parking bays in Dublin City Council.

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nitya123-github/Concrete-strength

Predicting the compressive strength of concrete using ML methods and Artificial Nueral Networks. Tools used in this project are Jupyter Notebook, UCI ML repository,Kaggle,Google colab.

Language: Jupyter Notebook - Size: 6.19 MB - Last synced at: 24 days ago - Pushed at: over 4 years ago - Stars: 11 - Forks: 5

Ehsan-Behzadi/Breast-Cancer-Prediction-Model

This project implements a machine learning model to predict breast cancer diagnosis. Utilizing techniques such as data preprocessing, feature selection, and various algorithms, the model aims to assist in early detection and improve healthcare outcomes. Explore the repository to understand the methodology and technologies used in this project.

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novianggita/Regularized-Regression

This project explores Regularized Regression techniques—Ridge and LASSO—to predict housing prices using the Boston Housing dataset

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joeyism/nnnba

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

Language: Python - Size: 51.4 MB - Last synced at: 20 days ago - Pushed at: almost 8 years ago - Stars: 10 - Forks: 3

k-miah/FSGLmstate

R package for variable selection via fused sparse-group lasso (FSGL) penalized multi-state models incorporating molecular data (Miah et al., 2024).

Language: R - Size: 450 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

dyavadi8769/University_Admission_Prediction

University Admission Predictor is a sophisticated Flask-based web application designed to predict the likelihood of admission to graduate programs based on student profiles. It leverages a range of regression techniques to evaluate admission chances.This project showcases the practical application of machine learning in educational forecasting.

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Joseph70234/Boston-Housing-Regression-Analysis

Linear regression analysis performed on Boston housing data.

Language: R - Size: 458 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

Emmanuelprz1400/Logistic-Regression

Project where the Logistic Regression algorithm is used

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englianhu/binary.com-interview-question

次元期权应征面试题范例。 #易经 #道家 #十二生肖 #姓氏堂号子嗣贞节牌坊 #天文历法 #张灯结彩 #农历 #夜观星象 #廿四节气 #算卜 #紫微斗数 #十二时辰 #生辰八字 #命运 #风水 《始祖赢政之子赢家黄氏江夏堂联富•秦谏——大秦赋》 万般皆下品，唯有读书高。🚩🇨🇳🏹🦔中科红旗，歼灭所有世袭制可兰经法家回教徒巫贼巫婆、洋番、峇峇娘惹。https://gitee.com/englianhu

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SaniyaAbushakimova/Machine-Learning-Algorithms-From-Scratch

Built core machine learning and statistical models from scratch in Python to deepen understanding of their underlying mathematics, without using high-level ML libraries. Tech: Python (numpy, pandas, seaborn, matplotlib, scipy, skmisc)

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Bhavnanahar/CAR.PRICE.PRED

"A machine learning model to predict the selling price of used cars based on various features like year, mileage, fuel type, and more. The project utilizes Linear Regression and Lasso Regression to provide accurate price estimates."

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MariiaSam/Rent-in-Brazil

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CassandraMaldonado/ML-Real-Estate-

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Ginga1402/Store_sales_Analysis_and_Profit_Prediction

Exploratory Data Analysis on Store Sales Data

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SravB/Computer-Vision-Weightlifting-Coach

Analyzes weightlifting videos for correct posture using pose estimation with OpenCV

Language: Jupyter Notebook - Size: 24 MB - Last synced at: about 2 months ago - Pushed at: about 6 years ago - Stars: 43 - Forks: 8

PhanChenh/PredictQuantity_PythonProject_PizzaDataset

Sales Quantity Forecasting for Pizza Dataset 2015

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Rizasaurus/Car-price-prediction-exercise-with-regression-model

Car price forecasting with one-variable, two-variable, three-variable, lasso, ridge, and elastic regression models

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sylvaincom/high-dimensional-statistics

[Python, R] My homeworks for the Statistics for high-dimensional data course of my MSc @ Mines Nancy

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the-bipu/algerian-fire-prediction

Algerian fire prediction with Linear Regression

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cbil-vt/iDDN

Multi-omics differential dependency network inference

Language: Python - Size: 2.78 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

je-suis-tm/machine-learning

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

Language: Jupyter Notebook - Size: 7.84 MB - Last synced at: 2 months ago - Pushed at: over 2 years ago - Stars: 234 - Forks: 51

tlverse/hal9001

🤠 📿 The Highly Adaptive Lasso

Language: R - Size: 13.1 MB - Last synced at: 7 days ago - Pushed at: 7 months ago - Stars: 50 - Forks: 15

grackner/dsc_210

Comparing Numerical Linear Algebra methods to predicting housing prices. Compares XG Boost, LASSO Regression and Newton's Method

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ShantiKumariGautam/QuickDepth

QuickDepth predicts the logic depth of RTL designs using machine learning, helping detect timing violations early. By analyzing design features like Fan-In and Gate Count, it optimizes designs before synthesis, saving time and improving efficiency.

Language: Python - Size: 50.8 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

SaniyaAbushakimova/Ames-Housing-Price-Prediction

Implemented regularized linear regression (Lasso, Ridge, ElasticNet) and tree-based models (Random Forest, XGBoost, CatBoost, LightGBM) to predict house prices in Ames, Iowa. The project explores feature engineering, outlier handling, and model tuning to improve predictive accuracy. Tech: Python (numpy, pandas, sklearn, catboost, os)

Language: Jupyter Notebook - Size: 3.56 MB - Last synced at: 7 days ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

vadimtyuryaev/RegrCoeffsExplorer

A tool for visualizing the coefficients of various regression models, taking into account empirical data distributions.

Language: R - Size: 5.65 MB - Last synced at: about 1 month ago - Pushed at: 5 months ago - Stars: 2 - Forks: 0

nickkunz/nestedhyperline

Nested Cross-Validation for Bayesian Optimized Linear Regularization

Language: Python - Size: 2.05 MB - Last synced at: 11 days ago - Pushed at: about 5 years ago - Stars: 2 - Forks: 0

Godm0de0n/Car-Price-Prediction

ML Model using Linear and Lasso Regression to Predict Car Prices and Comparing the Models

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ChaitanyaC22/House-Price-Prediction-Project-for-a-US-based-housing-company

The goal of this project is to garner data insights using data analytics to purchase houses at a price below their actual value and flip them on at a higher price. This project aims at building an effective regression model using regularization (i.e. advanced linear regression: Ridge and Lasso regression) in order to predict the actual values of prospective housing properties and decide whether to invest in them or not.

Language: Jupyter Notebook - Size: 3.97 MB - Last synced at: 3 months ago - Pushed at: almost 4 years ago - Stars: 4 - Forks: 1

PiotrTymoszuk/htGLMNET

High Throughput Light Weight Regularized Regression Modeling for Molecular Data

Language: R - Size: 43.4 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

Singhananddev/ML_SUPERVISED_LEARNING_SALES_PRIDICTION_PROJECT

ML_SUPERVISED_LEARNING_SALES_PRIDICTION_PROJECT

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sai-manas/FWI_Predictor_ML

Fire Weather Index (FWI) - Web App Predictor: Algerian Forest Fires dataset. Using Ridge, Lasso, Linear Regression, and ElasticNet models. Deployed as a Flask app on AWS Elastic Beanstalk. Explore the prediction insights for fire risk assessment.

Language: Jupyter Notebook - Size: 565 KB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 1

amruta33/End_to_End_Mlproject

The Students Performance Analysis project, is an insightful exploration of the factors that impact students' academic performance. Using a dataset containing various student attributes, the project aims to uncover patterns and relationships that influence their success in examinations. This analysis is particularly valuable for educators, policymak

Language: Jupyter Notebook - Size: 1.72 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

pngo1997/Multiple-Regression-and-Feature-Selection-Analysis

Explores multiple linear regression, feature selection, Ridge & Lasso regression, and Stochastic Gradient Descent (SGD) regression.

Language: Jupyter Notebook - Size: 1.26 MB - Last synced at: 4 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

rynanda/Regression-Classification-DeepNets

Regression analysing socio-economic data, multi-class classification of land types from spectral data, and training and adapting deep networks using the Street View House Numbers dataset.

Language: Jupyter Notebook - Size: 32.9 MB - Last synced at: 3 months ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

sorna-fast/Car-price-prediction-exercise-with-regression-model

Car price forecasting with one-variable, two-variable, three-variable, lasso, ridge, and elastic regression models

Language: Jupyter Notebook - Size: 1.46 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

ecthompsoncodes/FDS-Epi-Project

Machine learning project in collaboration with Sandia National Labs aimed at predicting COVID-19 hotspots during the early stages of the pandemic.

Language: Jupyter Notebook - Size: 28.5 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

Trigenaris/Baseball-Player-Salary-Prediction-with-Ridge-Lasso-and-ElasticNet

In this section, we will go through the Hitters dataset as firstly analyzing the data, then preprocessing it and lastly creating 3 different models which are Ridge Regression, Lasso Regression and ElasticNet Regression

Language: Jupyter Notebook - Size: 793 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

Tynab/Machine-Learning-Overview

CyberSoft Machine Learning 03 - Overview

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mr-kartal/ML_codes_CK

Machine learning code includes various regression techniques. By ↃK.

Language: Python - Size: 548 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

mischieff01/Project-Machine-Learning-Models

A collection of machine learning implementations for regression and classification tasks using Python and scikit-learn. Each model is detailed in Jupyter notebooks with explanations, code, and visualizations.

Language: Jupyter Notebook - Size: 1.22 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

garfsters/Real-Estate-Price-Prediction

Using OLS regression (and Ridge and Lasso to compare), we worked on a project that uses a dataset to predict housing prices based on user inputs on house details.

Language: Python - Size: 252 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

maettuu/23HS-Foundations-of-Data-Science

Repository for the course Foundation of Data Science Fall 2023

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dimasthoriq/cnc-machining-time-estimation

Developed for my undergrad thesis, academic purposes only

Language: Jupyter Notebook - Size: 7.18 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

KasiMuthuveerappan/IVY_League-Admission-LinearRegression

📗 This repository provides an in-depth exploration of the predictive linear regression model tailored for Jamboree Institute students' data, with the goal of assisting their admission to international colleges. The analysis encompasses the application of Ridge, Lasso, and ElasticNet regressions to enhance predictive accuracy and robustness.

Language: Jupyter Notebook - Size: 11.7 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

myahninsi/housing-price-prediction-ml

Final project for Big Data Visualization for Business Communications 01 (DSMM Group 1). Analyzes housing data, identifies key price factors, and builds predictive models using machine learning. Includes Power BI dashboards for interactive visualizations and Flask for deployment.

Language: Jupyter Notebook - Size: 11 MB - Last synced at: 24 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

Khushi130404/Regulexa

Regulexa is a Python project that showcases and compares Ridge, Lasso, and Elastic-Net regularization techniques in machine learning. It includes visualizations and performance insights to help prevent overfitting and improve model generalization.

Language: Jupyter Notebook - Size: 877 KB - Last synced at: 4 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

DolbyUUU/regression_algorithm_implementation_python

regression algorithm implementaion from scratch with python (least-squares, regularized LS, L1-regularized LS, robust regression)

Language: Python - Size: 4.88 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

brandonorodriguez/Unraveling-Socioeconomic-Factors-in-U.S.-Cancer-Incidence-A-Linear-Modeling-Approach

Unraveling Socioeconomic Factors in the U.S. Cancer Incidence : A Linear Modeling Approach

Language: R - Size: 6.05 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

Vitor-Garcia-Comissoli/Codes_from_MAE0501

Several programming exercises and a final project developed for a College class (MAE 0501 - Statistical Learning)

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JaewonSon37/Data_Analysis_and_Regression1

Language: R - Size: 7.47 MB - Last synced at: 3 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

juliahaas1/STAT-543-Midterm

The purpose of this project was to analyze traffic stop data and create a model to predict if when a search was conducted contraband will be found.

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SantiagoEnriqueGA/custom_linear_learning

This repository focuses on building linear regression algorithms from scratch using only Numpy for faster array processing.

Language: Python - Size: 1.53 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

cglamb/Modeling

Modeling Portfolio (Python based)

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Arek-KesizAbnousi/Neural_Networks

Fit four different neural networks: (a) Two distinct single hidden layer neural networks. (b) Two distinct neural networks with two hidden layers. Compare the accuracy of these four Neural networks among them. Also compare it to other classification methods.

Language: Python - Size: 2.93 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

johnnymdoubleu/lassoSSNAL

Semismooth Newton Augmented Langrangian Method implemented in R

Language: R - Size: 8.03 MB - Last synced at: 7 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

jacopo-tarantino/Market-Analysis-based-on-Machine-Learning-techniques

Implemented Feature Selection, Regularization, and Dimension Reduction, followed by Model Selection to predict sales and identify profitable markets for a retail firm.

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HuyNgo171099/Enrolment-Prediction

A machine learning project utilizing LASSO regression and Random Forest to predict student enrollment status based on historical application data

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ma-nadeau/NonlinearRegression_And_Regularization

Model evaluation by implementing a linear regression model from scratch using non-linear basis functions

Language: Python - Size: 147 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

EC4308/loan-default

Created a loan default classification model at the point of granting a loan

Language: HTML - Size: 226 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

Jazib-2004/Prediction-Classification-and-Clustering-on-Public-Expenses-Dataset

Applying end-to-end ML pipeline incl. EDA to get to know data more, data preprocessing to prepare data for modelling, and at last REGRESSION to predict one feature's value, CLASSIFICATION to classify one feature, and K-means for clustering and its analysis.

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oscarhoffmann3487/TDDE01_Machine_Learning

This repository contains lab-solutions for the TDDE01 Machine Learning course taken at Linköping University during the fall of 2023. The course includes three labs focusing on core ML concepts.

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juan-gamero-salinas/climateready-survey-pamplona

This repository gives you access to the CLIMATEREADY survey dataset containing thermal comfort votes during the 2021 and 2022 heatwave periods in Pamplona, Spain, as well as other relevant parameters self-reported by surveyees (e.g. occupant characteristics and behaviour, key building/dwelling characteristics, sleep problems, heat-related symptoms)

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antonior92/NarmaxLasso.jl

Algorithms for Lasso estimation of NARMAX models.

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GijsWerkman/startup-investment-analysis

Group project for the course Business Analytics Applications with Python for my MScBA in Business Analytics & Management.

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proxyflux/Football-player-price-prediction

Price Prediction with Lasso, Ridge, Random Forest, SVR, Gradient Boosting, KNN, Linear Regression, Logistic Regression

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shaadclt/Boston-House-Price-Prediction-LassoRegression

This project involves the prediction of house prices in Boston using Lasso Regression in Jupyter Notebook. The dataset contains features such as average number of rooms per dwelling, crime rate, and more. Through this analysis, we aim to build a regression model that accurately predicts house prices based on the given input features.

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dynamicanupam/Housing_Price_Prediction_using_Advanced_Regression

Build a regularized regression model to understand the most important variables to predict housing prices.

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Harshika-123/Machine_Learning

Machine Learning Algorithms

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Silvano315/Prediction-model-for-a-real-estate-market

This repository is the third project of the master's degree in AI Engineering that I am following. It aims toto optimize real estate price valuation through the use of advanced regularisation techniques in linear regression models by implementing Lasso, Ridge and Elastic Net in order to obtain accurate and stable price predictions.

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sudhanshusinghaiml/End-to-End-Real-Estate-Price-Prediction-Model

This project for price prediction of Real Estate Property. Model is trained on dataset with Property Price as the Target Variable. The model takes into account the important factors

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krishcy25/Building-several-Regression-MachineLearning-Algorithms-for-ContinuousOutcomePrediction

This repository focuses on building several Regression Models-Linear Regression, XGBoost Regressor, Ridge Regression, Lasso Regression, Polynomial Regression that predicts the continuous outcome (House Prices) along with several Data Preparation Techniques (Transformations/Scaling, Imputation, Filtering of Outliers, Handling of correlated features, One Hot Encoding)

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MahmoudNamNam/NYC_Taxi_Trip_Duration_Predection

The project aims to predict NYC taxi trip durations using advanced regression techniques. We utilized Polynomial Linear Regression, Ridge Regression, and Lasso Regression for feature extraction and achieved a validation R² score of 0.67. Feature engineering included KMeans clustering, Haversine distance calculation, and date-time feature extraction

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