Course project repo for DSGA 1004

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

Outlier detection in performance measurements

NumPy Practice Repository Dive into the world of numerical computing with our collection of NumPy exercises. Perfect for beginners and seasoned programmers alike, this repository offers a range of challenges to sharpen your array manipulation and data analysis skills.

Machine Learning lab course at the Technical University of Berlin. Covers supervised and unsupervised learning techniques.

The accompanying code to the publication "Out-of-Distribution Detection using Outlier Detection Methods"

Outliner Detection with Isolation Forest

Anomaly detection platform for time-series data developed during the WomenHackAI hackathon by Siemens Female Data Science Network

This repository contains code for predicting the price of mobile phones using regression models. It includes the implementation of various regression techniques such as Random Forest Regression, Decision Tree Regressor, Linear Regression, and Lasso Regression.

Car Sales Price Prediction (Streamlit)

We use machine learning and data analysis to predict resale prices of Singapore flats. Our documentation covers data preprocessing, feature engineering, regression, and model selection. Discover how we improved predictions to optimize solutions.

Mutation frequencies of COSMIC

Histogram Based Outlier Detection

Outlier Detection using Relevant Attributes published in Cluster Computing, Springer (2021)

Basics of Data Preprocessing.

Native Python implementation of the outlier detection method proposed by Basu and Meckesheimer.

Number of Neighbors and Contamination Tuning for Local Outlier Factor

This project utilizes Apache Spark for outlier detection on 2D point data, employing the K-means clustering algorithm. The K-means algorithm is leveraged to group normal data points, and outliers are identified based on their deviation from the established clusters.