Measures and metrics for image2image tasks. PyTorch.

Comparison of IQA models in Perceptual Optimization

💨 A desktop application to convert videos to high-quality GIF built with Electron and React

R enviroment - fast imputations 🐉

INSAID Assignment to create a ML model to detect fraud transactions for a financial company.

Terraform module to setup AWS Direct Connect resources

Assignment-05-Multiple-Linear-Regression-2. Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few y…

'21 한국통신학회 동계종합학술발표회 투고 논문, "XGBoost기반 당뇨병 예측 알고리즘 연구:2016~2018을 이용하여" 연구 과정 전반의 Open Archive입니다.

An intelligent video surveillance system also provides video cameras and recording solutions to monitor every part of the building and site perimeter. Yet it also utilizes smart security technology such as sensors and AI models.

Statistical concepts, from statistical inference to Bayes probability and different distribution types

Predictive model that tells important factors(or features) affecting the demand for shared bikes

This is a group project for MTH416A: Regression Analysis at IIT Kanpur

Machine Learning Project

Supervised Classfication models - Logistic Regression & Decision Tree, AUC-ROC Curve

This project uses the Reaction Time Survey dataset to develop a linear regression model for accurately predicting student reaction times based on various predictors. Tech: R (RStudio)

Prevendo Customer Churn em Operadoras de Telecom

Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Levera…

The objective of this project is to find the variables which most affect in predicting the price of a property from the data.

This is an contrast of linear regression model, used to examine the association between the independent variable(category or contineous) with dependent variable(binary), which is an discrete outcome.

Final Capstone project at Amsterdam University College. Analyzed house prices using hedonic regression and Neural Network.