Some method for working with time series, such as outliers tests, test of trend type, additive model of time series

Course project repo for DSGA 1004

Credit card fraud detection

This project aims to demonstrate the use of various data cleaning methods.

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

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

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

The performance of the machine learning algorithm also depends on properly detecting outliers in the dataset. Particularly the regression algorithms are very easily influenced by the outliers. In this case, if the dataset is not correctly cleaned by removing the outlier, then the model performance is unlikely to be as expected. PyOD - Python Too…

Данный проект направлен на демонстрацию применения различных методов очистки данных

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.