This is Algorithm repository of supervised learning and unsupervised learning

👩🏻‍🚀 13-DataMining: Clear, beginner-friendly explanations and hands-on resources on Principal Component Analysis (PCA) and Isolation Forest for Outlier Detection — designed to make unsupervised learning approachable for everyone. ✠💚✠

📊 Explore data mining with this guide on Principal Component Analysis (PCA) and Isolation Forest for effective dimensionality reduction and anomaly detection.

We will use Python and unsupervised learning techniques to predict whether cryptocurrencies are affected by 24-hour or 7-day price changes. We will perform clustering using K-means and optimize the clusters using Principal Component Analysis (PCA).

ML_Foundations series Part 2 - Intro to Unsupervised learning - PCA (Principal Component Analysis) & KDE (Kernel Density Estimation)

👩🏻‍🚀 10- DataMining- This repo implements the Mean Shift clustering algorithm, which finds clusters by shifting points toward higher density areas without needing a preset number of clusters. It includes implementation code, comparisons with K-Means, and applications like video tracking and face recognition.