Data Science & ML-Statistics

Implementation of statistics & data science algorithms for Machine Learning & Data Mining in python, using Numpy, Pandas & SKLearn. Data were extracted from MovieLens and Google Trends.

This repository includes algorithms and statistical methods for:

1. Data Visualization:

• Bar Plots
• Histogram Plot
• LogLog Plot
• Line Plot
• Pie Plot

2. Distribution Visualization

• Gaussian Distribution Plot
• Power Law Plot
• QQ Plot

3. Correlation Analysis

• Covariance
• Pearson Correlation
• Spearman Correlation
• Fisher-Z Transformation
• Kendall Correlation
• Weighted Kendall
• Cosine Similarit

4. Anomaly Detection (Outlier detection & removal)

• Isolation Forest
• Local Outlier Factor
• Elliptic Envelope
• DBSCAN
• PCA + DBSCAN

5. Data Scaling

• Min-Max
• Max-Abs
• Z-Score
• Robust-Scaling

6. Dimensionality Reduction (Image Compression Example)