DataScience stuff for Python

Analyzing a dataset to understand mental health factors, this project employs Python tools for preprocessing, exploration, segmentation, trend analysis, and modeling.

Temperature anomaly detection

Analyze motion sensor data to find patterns in a person's behavior

Machine Learning

Fraud Detection model based on anonymized credit card transactions based on Isolation Forest Algorithm and Local Outlier Factor

This project aims to detect credit card fraud using Anamoly detection techniques such as Isolation Forest and Local Outlier Factor algorithms.

Built a model to detect fraudulent credit card transactions so that the customers of credit card companies are not charged for items that they did not purchase.

The workflow includes data exploration, dimension reduction, and visualization, with the integration of machine learning concepts for advanced analysis. The GitHub repository provides comprehensive documentation and instructions for replicating the analysis and findings.

AnomalyFinder-AI is an AI tool for detecting and analyzing anomalies in log data from various systems and applications. It identifies irregular patterns, provides descriptions of anomalies, and suggests solutions to prevent issues.

Package provides java implementation of outlier detection algorithms for

Unsupervised machine learning model to predict fraudulent credit card transactions on a highly imbalanced dataset.

Credit card fraud detection

The project explores a range of methods, including both statistical analysis, traditional machine learning and deep learning approaches to anomaly detection a critical aspect of data science and machine learning, with a specific application to the detection of credit card fraud detection and prevention.

This project focuses on building a anomaly detection model to detect wafer runs that are anomalous. The dataset does not contain labelled data (anomalous/non-anomalous), therefore an unsupervised learning method is utilised. Python and the Sci-kitLearn machine learning libraries are the primary tools used in this project.