Course project repo for DSGA 1004

This repo contains a regression analysis of crime rates in the Boston area.

R codes for basic algorithms in Marketing models and multi variate statistics

This repository you are browsing contains intermediate level piece of codes which are useful for cleaning, exploratory analysis, handling of missing data points, outlier detection and different visualization techniques using graphics, ggplot2, tidycharts, ggExtra packages. Also in particular part of the script you can get basic information about…

Project split in 2 parts: Data cleaning & Exploratory data analysis (Use cleaned dataset built in part 1 to complete part 2)

A ML project with EDA and model that helps in predicting next-day rain by training classification models on the target variable RainTomorrow.

ACT project for the masters programme Geo-Information Science at Wageningen University & Research, conducted for the Dutch Ministry of Defence

Build a model using Linear Regression for Banglore Home Prices dataset, then write a python flask server that uses the saved model to serve http requests, then deploy the app to the Cloud(AWS EC2)

Repository for code release of preprint: "Repairing Systematic Outliers by Learning Clean Subspaces in VAEs".

👾 Outlier Exposure with Generative Models

Данный проект направлен на демонстрацию применения различных методов очистки данных

Data Science - Multi Linear Regression Work

HH applicant data research, cleaning and outliers detecting

an R project of manipulating and fittingdata into regression with 95.5% R-Square, involving Automated Selection, detecting outliers, influential observations and multicollinearity

The repository contains implementations of different univariate outlier detection algorithms

Detecting anomaly transactions in credit card using classification and Outlier Detection.

An outlier-detection algorithm which assigns a high and low value to the points, the higher or lower each value is means that it's the most potential outlier.

This repository contains an implementation for Flight delay forecasting using different machine learning models such as linear regression, polynomial regression, and regularizing based on lasso regression. It is also the solution for Assignment1 in Machine Learning course for ROCV master's program at Innopolis University.