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Machine Learning Journey

Hello, I'm Kavin 👋
I'm a BCA student learning Machine Learning with a strong focus on fundamentals, algorithms, and practical implementation.

This repository documents my step-by-step progress in Machine Learning, from data preprocessing to supervised and highlighting unsupervised learning models.

📂 Repository Structure

1: Data Preprocessing

  • Handling missing values
  • Encoding categorical data
  • Column Transformer
  • Pipelines
  • Train-test split

2: Supervised Learning

  • Linear Regression
  • Logistic Regression
  • KNN
  • Naive Bayes
  • Decision Tree (with visualization)
  • Random Forest

3: Unsupervised Learning

  • K-Means Clustering
  • Hierarchical Clustering
  • DBSCAN Clustering

Learning Approach

  • Understand theory
  • Implement using Python & scikit-learn
  • Apply on real datasets
  • Evaluate and analyze results

Tools & Libraries

  • Python
  • NumPy, Pandas
  • Matplotlib, Seaborn, plotly
  • Scikit-learn

This repository will be continuously updated as I progress further in ML & Deep Learning.