In this repo, different techniques will be done to analyze Anomaly detection

This repository focuses on implementing various machine learning techniques for Intrusion Detection Systems (IDS) in cybersecurity. It includes Jupyter Notebooks demonstrating methods like Isolation Forest, K-Means clustering, and Principal Component Analysis (PCA). Written in Python, it provides practical insights into anomaly detection.

Comparison of various anomaly detection algorithms using scikit-learn and visualization through Plotly Dash