outlierdetection

This repository contains three Knime workflows that aim to analyze the Air Traffic Passenger Statistics dataset from the San Francisco International Airport. The workflows include tasks such as classification comparison, regression analysis, and outlier detection using various machine learning techniques.

The comprehensive study that investigates the implementation of machine learning algorithms for fraud detection in e-commerce using Python.

outlier detection for supply chain and logistics

A collection of essential machine learning algorithms implemented from scratch and with libraries. Ideal for students and beginners to understand core ML concepts through hands-on examples.

My list of EDA And ML exercises

📊 A Customer Credit Risk dataset collected from multiple sources (CSV, JSON, SQL, and an external API). perform full-scale preprocessing and feature engineering so that the dataset is clean, consistent, and suitable for building a Machine Learning model that predicts whether a customer is likely to default on a loan.